This paper uses an improved deep learning algorithm to judge the rationality of the design of landscape image feature recognition. The preprocessing of the image is proposed to enhance the data. The deficiencies in landscape feature extraction are further addressed based on the new model. Then, the two-stage training method of the model is used to solve the problems of long training time and convergence difficulties in deep learning. Innovative methods for zoning and segmentation training of landscape pattern (...) features are proposed, which makes model training faster and generates more creative landscape patterns. Because of the impact of too many types of landscape elements in landscape images, traditional convolutional neural networks can no longer effectively solve this problem. On this basis, a fully convolutional neural network model is designed to perform semantic segmentation of landscape elements in landscape images. Through the method of deconvolution, the pixel-level semantic segmentation is realized. Compared with the 65% accuracy rate of the convolutional neural network, the fully convolutional neural network has an accuracy rate of 90.3% for the recognition of landscape elements. The method is effective, accurate, and intelligent for the classification of landscape element design, which better improves the accuracy of classification, greatly reduces the cost of landscape element design classification, and ensures that the technical method is feasible. This paper classifies landscape behavior based on this model for full convolutional neural network landscape images and demonstrates the effectiveness of using the model. In terms of landscape image processing, the image evaluation provides a certain basis. (shrink)

The image of St. Petersburg is an integral part of Russian art, in particular, in watercolor painting. This article is devoted to the analysis of the work of Russian watercolor artists, identifying the specifics and characteristic features of the image of the city on the Neva in their work. The object of the study is watercolors by Russian artists, the subject is expressive means, techniques and methods through which the image of St. Petersburg is embodied. On (...) the example of watercolor works by E.P. Gau, I.A. Vladimirova, A.S. Vedernikov, A.P. Ostroumova-Lebedeva, P.P. Grigoryants, G.P. Fitingof, A. Ermolaev, V.V. Proshkin, K. Kuzema, V. Kolbasov, O. Litvinenko, etc. the historical transformation of the artistic image of St. Petersburg, its conditionality by cultural and historical factors and the nature of the life of the inhabitants of the city is shown. The study concluded that the image of St. Petersburg is important for Russian artists, as well as a significant variety of its creative interpretations. Each watercolor work demonstrates the subjective attitude of artists to St. Petersburg, thanks to which real urban landscapes acquire spirituality and unique expressiveness. The complex historical fate of this cultural and artistic center of Russia, which was once a magnificent capital, experienced revolutionary events and went through military destruction, determined the versatility of creative approaches to the embodiment of the city, as a result of various turns of history, it lost, then regained its greatness, beauty and attractiveness. Petersburg in watercolors is invariably filled with vitality, lyrical feelings and the love of artists. (shrink)

This paper proposes underwater target identification with local features and a feature tracking algorithm for acoustic image sequences. Feature detectors and descriptors are key to feature tracking. Their performance in underwater scene is evaluated by the change of multitarget parameters. A comprehensive quantitative investigation into the performance of feature tracking is thereby presented. Experimental results confirm that the proposed algorithm can accurately track potential targets and determine whether the potential targets are static targets, dynamic targets, or false alarms (...) according to the tracking trajectories and statistical data. (shrink)

For unmanned aerial vehicle, object detection at different scales is an important component for the visual recognition. Recent advances in convolutional neural networks have demonstrated that attention mechanism remarkably enhances multiscale representation of CNNs. However, most existing multiscale feature representation methods simply employ several attention blocks in the attention mechanism to adaptively recalibrate the feature response, which overlooks the context information at a multiscale level. To solve this problem, a multiscale feature filtering network is proposed in this paper for (...) class='Hi'>image recognition system in the UAV. A novel building block, namely, multiscale feature filtering module, is proposed for ResNet-like backbones and it allows feature-selective learning for multiscale context information across multiparallel branches. These branches employ multiple atrous convolutions at different scales, respectively, and further adaptively generate channel-wise feature responses by emphasizing channel-wise dependencies. Experimental results on CIFAR100 and Tiny ImageNet datasets reflect that the MFFNet achieves very competitive results in comparison with previous baseline models. Further ablation experiments verify that the MFFNet can achieve consistent performance gains in image classification and object detection tasks. (shrink)

Brain tumor classification plays a niche role in medical prognosis and effective treatment process. We have proposed a combined feature and image-based classifier for brain tumor image classification in this study. Carious deep neural network and deep convolutional neural networks -based architectures are proposed for image classification, namely, actual image feature-based classifier, segmented image feature-based classifier, actual and segmented image feature-based classifier, actual image-based classifier, segmented image-based classifier, actual and segmented image-based (...) classifier, and finally, CFIC. The Kaggle Brain Tumor Detection 2020 dataset has been used to train and test the proposed classifiers. Among the various classifiers proposed, the CFIC performs better than all other proposed methods. The proposed CFIC method gives significantly better results in terms of sensitivity, specificity, and accuracy with 98.86, 97.14, and 98.97%, respectively, compared with the existing classification methods. (shrink)

In face recognition systems, highly robust facial feature representation and good classification algorithm performance can affect the effect of face recognition under unrestricted conditions. To explore the anti-interference performance of convolutional neural network reconstructed by deep learning framework in face image feature extraction and recognition, in the paper, first, the inception structure in the GoogleNet network and the residual error in the ResNet network structure are combined to construct a new deep reconstruction network algorithm, with the random gradient descent (...) and triplet loss functions as the model optimizer and classifier, respectively, and it is applied to the face recognition in Labeled Faces in the Wild face database. Then, the portrait pyramid segmentation and local feature point segmentation are applied to extract the features of face images, and the matching of face feature points is achieved using Euclidean distance and joint Bayesian method. Finally, Matlab software is used to simulate the algorithm proposed in this paper and compare it with other algorithms. The results show that the proposed algorithm has the best face recognition effect when the learning rate is 0.0004, the attenuation coefficient is 0.0001, the training method is SGD, and dropout is 0.1, and the algorithm proposed in this paper has the largest mean average precision compared to other CNN algorithms. The correct rate of face feature matching of the algorithm proposed in this paper is 84.72%, which is higher than LetNet-5, VGG-16, and VGG-19 algorithms, the correct rates of which are 6.94%, 2.5%, and 1.11%, respectively, but lower than GoogleNet, AlexNet, and ResNet algorithms. At the same time, the algorithm proposed in this paper has a faster matching time and a higher correct matching rate than the joint Bayesian method, indicating that the deep reconstruction network algorithm proposed in this paper can be used in face image recognition, FE, and matching, and it has strong anti-interference. (shrink)

As one of the most widely used methods in deep learning technology, convolutional neural networks have powerful feature extraction capabilities and nonlinear data fitting capabilities. However, the convolutional neural network method still has disadvantages such as complex network model, too long training time and excessive consumption of computing resources, slow convergence speed, network overfitting, and classification accuracy that needs to be improved. Therefore, this article proposes a dense convolutional neural network classification algorithm based on texture features for images in (...) virtual reality videos. First, the texture feature of the image is introduced as a priori information to reflect the spatial relationship between pixels and the unique characteristics of different types of ground features. Second, the grey level cooccurrence matrix is used to extract the grey level correlation features of the image in space. Then, Gauss Markov Random Field is used to establish the statistical correlation characteristics between neighbouring pixels, and the extracted GLCM-GMRF texture feature and image intensity vector are combined. Finally, based on DenseNet, an improved shallow layer dense convolutional neural network is proposed, which can compress network parameters and improve the feature extraction ability of the network. The experimental results show that compared with the current classification method, this method can effectively suppress the influence of coherent speckle noise and obtain better classification results. (shrink)

Learning a deep structure representation for complex information networks is a vital research area, and assessing the quality of stereoscopic images or videos is challenging due to complex 3D quality factors. In this paper, we explore how to extract effective features to enhance the prediction accuracy of perceptual quality assessment. Inspired by the structure representation of the human visual system and the machine learning technique, we propose a no-reference quality assessment scheme for stereoscopic images. More specifically, the statistical (...) class='Hi'>features of the gradient magnitude and Laplacian of Gaussian responses are extracted to form binocular quality-predictive features. After feature extraction, these features of distorted stereoscopic image and its human perceptual score are used to construct a statistical regression model with the machine learning technique. Experimental results on the benchmark databases show that the proposed model generates image quality prediction well correlated with the human visual perception and delivers highly competitive performance with the typical and representative methods. The proposed scheme can be further applied to the real-world applications on video broadcasting and 3D multimedia industry. (shrink)

The senses present their content in the form of images, three-dimensional arrays of located sense features. Peacocke’s “scenario content” is one attempt to capture image content; here, a richer notion is presented, sensory images include located objects and features predicated of them. It is argued that our grasp of the meaning of these images implies that they have propositional content. Two problems concerning image content are explored. The first is that even on an enriched conception, (...) class='Hi'>image content has certain expressive limitations. In particular, it cannot express absolute location and time (as opposed to spatiotemporal relations) or logical complexity. Yet, perceptual experience does seem to express certain absolute locations—namely, here and now. How can it do so? Secondly, image content cannot exhaust the significance of perceptual states. This is proved by noting that perception, memory, and anticipation can have the same image content. Yet they have different significance. These problems show that some of the significance of sensory states comes from outside the image. (shrink)

My aim in this paper is to offer a systematic analysis of a feature of Kant’s theory of perception that tends to be overlooked, viz., his account of how the imagination forms images in perception. Although Kant emphasizes the centrality of this feature of perception, indeed, calling it a ‘necessary ingredient’ of perception, commentators have instead focused primarily on his account of sensibility and intuitions on the one hand, and understanding and concepts on the other. However, I show that careful (...) attention to what he says about the nature of images, their connection to the imagination, and their role in perception in his Metaphysics Lectures, as well as in the Deduction and Schematism chapters of the first Critique reveals that Kant is working with a richer, more nuanced framework for perception than is often attributed to him. I contend that it is only once we have a revised framework for Kant’s theory of perception in place that we will be able to make further headway in debates, e.g., about whether or not he is a conceptualist about perception. (shrink)

Transfer learning can improve the robustness of deep learning in the case of small samples. However, when the semantic difference between the source domain data and the target domain data is large, transfer learning easily introduces redundant features and leads to negative transfer. According the mechanism of the human brain focusing on effective features while ignoring redundant features in recognition tasks, a brain-like classification method based on adaptive feature matching dual-source domain heterogeneous transfer learning is proposed for (...) the preoperative aided diagnosis of lung granuloma and lung adenocarcinoma for patients with solitary pulmonary solid nodule in the case of small samples. The method includes two parts: (1) feature extraction and (2) feature classification. In the feature extraction part, first, By simulating the feature selection mechanism of the human brain in the process of drawing inferences about other cases from one instance, an adaptive selected-based dual-source domain feature matching network is proposed to determine the matching weight of each pair of feature maps and each pair of convolution layers between the two source networks and the target network, respectively. These two weights can, respectively, adaptive select the features in the source network that are conducive to the learning of the target task, and the destination of feature transfer to improve the robustness of the target network. Meanwhile, a target network based on diverse branch block is proposed, which made the target network have different receptive fields and complex paths to further improve the feature expression ability of the target network. Second, the convolution kernel of the target network is used as the feature extractor to extract features. In the feature classification part, an ensemble classifier based on sparse Bayesian extreme learning machine is proposed that can automatically decide how to combine the output of base classifiers to improve the classification performance. Finally, the experimental results (the AUCs were 0.9542 and 0.9356, respectively) on the data of two center data show that this method can provide a better diagnostic reference for doctors. (shrink)

In this work, a system for the classification of liver dynamic contest- enhanced CT images is presented. The system simultaneously analyzes the images with the same slice location, corresponding to three typical acquisition moments. At first, the texture features are extracted separately for each acquisition mo- ment. Afterwards, they are united in one “multiphase” vector, characterizing a triplet of textures. The work focuses on finding the most appropriate features that characterize a multi-image texture. At the beginning, the (...) features which are unstable and dependent on ROI size are eliminated. Then, a small subset of remaining features is selected in order to guarantee the best possible classification accuracy. In total, 9 extraction methods were used, and 61 features were calculated for each of three acquisition moments. 1511 texture triplets, corresponding to 4 hepatic tissue classes were recognized. As a classifier, an adaptive boosting algorithm with a C4.5 tree was used. Experiments show that a small set of 12 features is able to ensure classification accuracy exceeding 90%, while all of the 183 features provide an accuracy rate of 88.94%. (shrink)

The luminous value is high for many natural scenes, which causes loss of information and occurs in dark images. The High Dynamic Range (HDR) technique captures the same objects or scene for multiple times in different exposure and produces the images with proper illumination. This technique is used in the various applications such as medical imaging and observing the skylight, etc. HDR imaging techniques usually have the issue of lower efficiency due to capturing of multiple photos. In this paper, an (...) efficient method is proposed for HDR imaging technique to achieve better performance and lower noise. The Luminance-Chrominance-Gradient High Dynamic Range (LCGHDR) method is proposed to obtain the proper luminous value of images. The same scenario is captured at different exposure are processed by the proposed method. Based on these feature values extracted from the different images and exposure fusion technique was developed that helps for the proper imaging. This experiment was evaluated and analyzed by comparing with the other methods, which showed the efficiency of the proposed method. This method needs only 124.594 seconds for the computation, while existing method need 139.869 seconds for the same number of images. (shrink)

Given that many imaging technologies in biology and medicine are non-optical and generate data that is essentially numerical, it is a striking feature of these technologies that the data generated using them are most frequently displayed in the form of semi-naturalistic, photograph-like images. In this paper, I claim that three factors underlie this: (1) historical preferences, (2) the rhetorical power of images, and (3) the cognitive accessibility of data presented in the form of images. The third of these can be (...) argued to provide an epistemic advantage to images, but I will further argue that this is often misleading and that images can in many cases be less informative than the corresponding mathematical data. (shrink)

How do pictures represent? In this book Robert Hopkins casts new light on an ancient question by connecting it to issues in the philosophies of mind and perception. He starts by describing several striking features of picturing that demand explanation. These features strongly suggest that our experience of pictures is central to the way they represent, and Hopkins characterizes that experience as one of resemblance in a particular respect. He deals convincingly with the objections traditionally assumed to be (...) fatal to resemblance views, and shows how his own account is uniquely well placed to explain picturing's key features. His discussion engages in detail with issues concerning perception in general, including how to describe phenomena that have long puzzled philosophers and psychologists, and the book concludes with an attempt to see what a proper understanding of picturing can tell us about that deeply mysterious phenomenon, the visual imagination. (shrink)

After-images, I believe, hold the key to certain much-debated issues regarding meaning and verification. In particular, an analysis of the relevant features of our discourse shows that views often held to be untenable or unintelligible or avoidable regarding our discourse about pain and similar sensations are not so easily escaped in the context of after-images.

With the increasing scale of e-commerce, the complexity of image content makes commodity image classification face great challenges. Image feature extraction often determines the quality of the final classification results. At present, the image feature extraction part mainly includes the underlying visual feature and the intermediate semantic feature. The intermediate semantics of the image acts as a bridge between the underlying features and the advanced semantics of the image, which can make up for (...) the semantic gap to a certain extent and has strong robustness. As a typical intermediate semantic representation method, the bag-of-visual-words model has received extensive attention in image classification. However, the traditional BoVW model loses the location information of local features, and its local feature descriptors mainly focus on the texture shape information of local regions but lack the expression of color information. Therefore, in this paper, the improved bag-of-visual-words model is presented, which contains three aspects of improvement: multiscale local region extraction; local feature description by speeded up robust features and color vector angle histogram ; and diagonal concentric rectangular pattern. Experimental results show that the three aspects of improvement to the BoVW model are complementary, while compared with the traditional BoVW and the BoVW adopting SURF + SPM, the classification accuracy of the improved BoVW is increased by 3.60% and 2.33%, respectively. (shrink)

Radiography images are widely utilized in the health sector to recognize the patient health condition. The noise and irrelevant region information minimize the entire disease detection accuracy and computation complexity. Therefore, in this study, statistical Kolmogorov–Smirnov test has been integrated with wavelet transform to overcome the de-noising issues. Then the cat swarm-optimized deep belief network is applied to extract the features from the affected region. The optimized deep learning model reduces the feature training cost and time and improves the (...) overall disease detection accuracy. The network learning process is enhanced according to the AdaDelta learning process, which replaces the learning parameter with a delta value. This process minimizes the error rate while recognizing the disease. The efficiency of the system evaluated using image retrieval in medical application dataset. This process helps to determine the various diseases such as breast, lung, and pediatric studies. (shrink)

A social network image denoising algorithm based on multifeature fusion is proposed. Based on the multifeature fusion theory, the process of social network image denoising is regarded as the fitting process of neural network, and a simple and efficient convolution neural structure of multifeature fusion is constructed for image denoising. The gray features of social network image are collected, and the gray values are denoising and cleaning. Based on the image features, multiple denoising (...) is carried out to ensure the accuracy of social network image denoising algorithm and improve the accuracy of image processing. Experiments show that the average noise of the image processed by the algorithm designed in this study is reduced by 8.6905 dB, which is much larger than that of other methods, and the signal-to-noise ratio of the output image is high, which is maintained at about 30 dB, which has a high effect in the process of practical application. (shrink)

Some photographs show determinate features of a scene because the photographed scene had those features. This dependency relation is, rightly, a consensus in philosophy of photography. I seek to refute many long-established theories of photography by arguing that they are incompatible with this commitment. In Section II, I classify accounts of photography as either single-stage or multi-stage. In Section III, I analyze the historical basis for single-stage accounts. In Section IV, I explain why the single-stage view led scientists (...) to postulate “latent” photographic images as a technical phenomenon in early chemical photography. In Section V, I discredit the notion of an invisible latent image in chemical photography and, in Section VI, extend this objection to the legacy of the latent image in digital photography. In Section VII, I appeal to the dependency relation to explain why the notion of a latent image makes the single-stage account untenable. Finally, I use the multi-stage account to advance debate about “new” versus “orthodox” theories of photography. (shrink)

From a twenty-first century partnership between bioethics and neuroscience, the modern field of neuroethics is emerging, and technologies enabling functional neuroimaging with unprecedented sensitivity have brought new ethical, social and legal issues to the forefront. Some issues, akin to those surrounding modern genetics, raise critical questions regarding prediction of disease, privacy and identity. However, with new and still-evolving insights into our neurobiology and previously unquantifiable features of profoundly personal behaviors such as social attitude, value and moral agency, the difficulty (...) of carefully and properly interpreting the relationship between brain findings and our own self-concept is unprecedented. Therefore, while the ethics of genetics provides a legitimate starting point - even a backbone - for tackling ethical issues in neuroimaging, they do not suffice. Drawing on recent neuroimaging findings and their plausible real-world applications, we argue that interpretation of neuroimaging data is a key epistemological and ethical challenge. This challenge is two-fold. First, at the scientific level, the sheer complexity of neuroscience research poses challenges for integration of knowledge and meaningful interpretation of data. Second, at the social and cultural level, we find that interpretations of imaging studies are bound by cultural and anthropological frameworks. In particular, the introduction of concepts of self and personhood in neuroimaging illustrates the interaction of interpretation levels and is a major reason why ethical reflection on genetics will only partially help settle neuroethical issues. Indeed, ethical interpretation of such findings will necessitate not only traditional bioethical input but also a wider perspective on the construction of scientific knowledge. (shrink)

Purpose. Based on the study of philosophical anthropological concepts, to highlight the project of personality in different historical periods, to reveal the meaning of humanistic issues in the postmodern epoch, to identify the essential features of the image of human of the second half of the XX the beginning of the XXI century. Theoretical basis. The methodological basis of the article is the principles of historicism, integrity, objectivity regarding the mastery of the issue of person’s image in (...) postmodernism. The research applied comparative-historical, culturological, analytical, axiological approaches to reveal the problem of individuality in the second half of the XX the beginning of the XXI century. The theoretical basis of the article consists of scientific works in the field of philosophical anthropology, history, cultural studies, and aesthetics. Originality. The author revealed the peculiarities of transformation of the personality model from antiquity to postmodernism, specified the image of man of the second half of the XX the beginning of the XXI century. Conclusions. The analysis of anthropological ideas of Western philosophy of different ages shows the variety of views about understanding the nature of the person, its complexity and ambiguity. In the epoch of postmodernism humanistic issues are of particular relevance, which is connected with social and political uncertainty, domination of mass consciousness, loss of national and cultural identity. The image of a person of this period is deprived of a solid foundation, it is blurred and relative. The destruction of faith in the absolute in the context of the second half of the twentieth century contributed to the formation of confidence in the interdependence of all things, raised the problem of the personality image to a new ontological level. Orientation in the achievements of European civilization, perception of its anthropological experience, intercultural dialogue contribute to the productive use of the achievements of mankind in order to understand the modern person and to form its adequate image. In its essence, postmodernism does not set the goal to realize a retrospection of subject type. However, separating from the cultural memory the excerpts of ideas about a person, by certain styles and directions, it builds on their formations its own eclectic image of the individual. (shrink)

The body image with respect to physical disability has long been a woefully under-theorized area of scholarship. The literature that does attend to the body image in cases of physical abnormality or functional impairment regularly offer poorly articulated or problematic definitions of the concept, effectively undermining its historic analytic scope and depth. Here, I revisit the epistemic roots of the body image while also engaging the rich contemporary literature from a body studies perspective in order to situate (...) the narratives of amputees about the relationship between dismemberment, prosthetization, phantom limb syndrome, and body image. Stories about living with artificial, fleshy, phantomed, and residual limbs unquestionably reveal a number of peculiarities unique to amputees. However, they also offer a distinctively productive ingress into the analytic utility of a ‘re-visioned’ conceptualization of the body image more broadly speaking. Indeed, the body image can function as a robust investigative tool for exploring the intersubjective, processual, and relational features of embodiment and corporeality. (shrink)

This article continues the author's research devoted to the study of the problem of choreographic interpretations of literary works, in particular, John Neumeier's ballet "Anna Karenina". In this work, the identification of expressive staging means and choreographic elements used by Neumeier in the production of duets by Anna Karenina and Alexei Vronsky is carried out in order to determine the place of these choreographic fragments in the performance, as well as their significance for the author's interpretation of the images of (...) the main characters of the novel by Leo Tolstoy. In the course of the research, the author applied comparative-historical, ideological-artistic and analytical methods, as well as the method of included observation. In the course of the source analysis, video materials from the archives of the Hamburg Ballettzentrum and the Moscow Bolshoi Theater were used, as well as lectures conducted by Neumeier before the Moscow premiere of Anna Karenina. A detailed analysis of the dance score of three duets by Anna and Vronsky revealed traditional and innovative author's solutions related to the new research results. So, Neumeier uses such staging means as the compilation of Tchaikovsky and Schnittke's music; the inclusion of symbolic images in the choreographic canvas; the appearance of other characters; the use of stage lighting to accentuate the transition from reality to the sphere of the subconscious; active choreographic development based on a technically saturated duet dance, replete with high supports in the neoclassical style, as well as acrobatic elements; semantic use of plastic quotations. It can be concluded that in order to develop the images and relationships of Anna Karenina and Alexey Vronsky, the choreographer chooses a duet as the dominant musical and choreographic form. Moreover, in his version of Anna Karenina, Neumeier makes three duets of the main characters a key component of the performance and the author's interpretation of the images of the main characters. (shrink)

A growing number of research misconduct cases handled by the Office of Research Integrity involve image manipulations. Manipulations may include simple image enhancements, misrepresenting an image as something different from what it is, and altering specific features of an image. Through a study of specific cases, the misconduct findings associated with image manipulation, detection methods and those likely to identify such manipulations, are discussed. This article explores sanctions imposed against guilty researchers and the factors (...) that resulted in no misconduct finding although relevant images clearly were flawed. Although new detection tools are available for universities and journals to detect questionable images, this article explores why these tools have not been embraced. (shrink)

Typical accounts of imagistic content have focused on the apparent analog character or continuous variability of images. In contrast, I consider the distinctive features of digital images, those composed of finite sets of discrete pixels. A rich source of evidence on digital imagistic content is found in the content-preserving algorithms that resize and reproduce digital images on computer screens and printers. I argue that these algorithms reveal a distinctive structural feature: digital images are always compositional (their parts contribute systematically (...) to overall content), but never inverse compositional (atomic parts may be replaced nonsynonymously without changing content). This indicates a sharp contrast with linguistic representations, which may or may not be compositional, and may or may not be inverse compositional. I argue this result sheds new light on the claim that imagistic content is inherently perspectival. (shrink)

Chinese animation of the beginning of the XXI century shows significant progress. A number of cartoons and animated series have been released. The hypothesis of the study is that their imagery, plots, and artistic features differ from foreign cartoons and gradually acquire a national identity. This process began in the 2000s, and its pace is only increasing, while it arouses interest from foreign studies, including Russian ones. The typological analysis of the images of the characters of famous Chinese cartoons (...) created at the beginning of the XXI century, as well as the analysis of stylistic and artistic features used by the authors to convey the uniqueness of the character, as well as to emphasize its belonging to Chinese culture, is the main problem of the article. The purpose of this research is to study the specifics of modern Chinese cartoon characters, to identify the features of the development process and the formation of their individual traits in accordance with national characteristics. Chinese animators tend to use the language of traditional art, attributes and symbols characteristic of the national culture. An appeal to the analysis of modern cartoon pictures allows us to highlight the main features of animated characters "with Chinese specifics". In addition, it is of interest to compare the features of the formation of images associated with China in foreign animated films and the characteristic features of characters appearing in the works of modern Chinese animators. (shrink)

Representations of the active brain have served to establish a particular domain of competence for brain mappers and to distinguish brain mapping’s particular contributions to mind/brain research. At the heart of the claims about the emerging contributions of functional brain mapping is a paradox: functional imagers seem to reject representations while also using them at multiple points in their work. This article therefore considers a love-hate relationship between scientists and their object: the case of the iconoclastic imager. This paradoxical stance (...) is the result of the formation of an interdisciplinary approach that brings together a number of scientific traditions and their particular standards of what constitutes scientific evidence. By examining the various ways in which images are deployed and rejected, the origins of these conflicting tendencies can be traced to the technological, methodological, and institutional elements in the work of functional imagers. This approach provides insight into the current demarcation of imaging and reflects on features of visual knowledge. (shrink)

The subject of the study is the consideration of modern trends in the study of fine art, in particular Russian portrait and narrative painting of the beginning of the XXI century. The object is scientific works related to various fields of the humanities, namely: art history, aesthetics, anthropology, sociology, philosophy, psychology, etc. Using their material, it is possible to show not only the difference in approaches to understanding the essence and role of the image of a modern person in (...) the art process, but also to demonstrate the specifics of the artistic interpretation of this figurative system in the context of art criticism, cultural and philosophical issues. Such a study allows us to systematize existing ideas about the peculiarities of the development of anthropological subjects in the mainstream of contemporary fine art in modern Russia, to identify the main directions. The main methodological basis of the study was a systematic approach that allowed us to consider contemporary Russian art as a single system. This helped to compare the approaches of modern researchers analyzing the place and role of the human image in it. Through the postmodern paradigm of perception and interpretation of anthropological topics, to identify the essential features of the ideas of Russian scientists. Methods of art historical analysis were also used. The starting point of the research is that at the moment in Russian science there is a body of art history and cultural studies devoted to the development of contemporary art in the country. However, there are no works summarizing the existing experience of scientists and defining the main directions of scientific thought. In light of this, the scientific novelty of the article lies in expanding the understanding of the methodological apparatus necessary for the analysis of the anthropological trend in the visual arts of our time, which is a promising path for future research in this area. The most demanded conceptual philosophical and historical-cultural foundations for the analysis and solution of practical problems in the field of contemporary art in relation to the representation of the human image are identified. Empirical research material has been collected and analyzed. (shrink)

Hinduism comprises perhaps the major cluster of religio-cultural traditions of India, and it can play a valuable role in helping us understand the nature of religion and human responses to life. Hindu image-worship lies at the core of what counts for Hinduism - up-front and subject to much curiosity and misunderstanding, yet it is a defining feature of this phenomenon. This book focuses on Hindu images and their worship with special reference to Vaiṣṇavism, a major strand of Hinduism. Concentrating (...) largely, but not exclusively, on Sanskritic source material, the author shows in the course of the book that Hindu image-worship may be understood via three levels of interpretation: the metaphysical/theological, the narratival or mythic, and the performative or ritual. Analysing the chief philosophical paradigm underlying Hindu image-worship and its implications, the book exemplifies its widespread application and tackles, among other topics such as the origins of image-worship in Hinduism, the transition from Vedic to image worship, a distinguishing feature of Hindu images: their multiple heads and limbs. Finally, with a view to laying the grounds for a more positive dialogic relationship between Hinduism and the "Abrahamic" faiths, which tend to condemn Hindu image-worship as "idolatry", the author examines the theological explanation and justification for embodiment of the Deity in Hinduism and discusses how Hinduism might justify itself against such a charge. Rich in Indological detail, and with an impressive grasp of the philosophical and theological issues underlying Hindu material culture, and image-worship, this book will be of interest to academics and others studying theology, Indian philosophy and Hinduism. (shrink)

Judging similarities among objects, events, and experiences is one of the most basic cognitive abilities, allowing us to make predictions and generalizations. The main assumption in similarity judgment is that people selectively attend to salient features of stimuli and judge their similarities on the basis of the common and distinct features of the stimuli. However, it is unclear how people select features from stimuli and how they weigh features. Here, we present a computational method that helps (...) address these questions. Our procedure combines image-processing techniques with a machine-learning algorithm and assesses feature weights that can account for both similarity and categorization judgment data. Our analysis suggests that a small number of local features are particularly important to explain our behavioral data. (shrink)

Luminescence‐based sensing schemes for oxygen have experienced a fast growth and are in the process of replacing the Clark electrode in many fields. Unlike electrodes, sensing is not limited to point measurements via fiber optic microsensors, but includes additional features such as planar sensing, imaging, and intracellular assays using nanosized sensor particles. In this essay, I review and discuss the essentials of (i) common solid‐state sensor approaches based on the use of luminescent indicator dyes and host polymers; (ii) fiber (...) optic and planar sensing schemes; (iii) nanoparticle‐based intracellular sensing; and (iv) common spectroscopies. Optical sensors are also capable of multiple simultaneous sensing (such as O2 and temperature). Sensors for O2 are produced nowadays in large quantities in industry. Fields of application include sensing of O2 in plant and animal physiology, in clinical chemistry, in marine sciences, in the chemical industry and in process biotechnology. (shrink)

This paper is focused on the ways of expressing trust and distrust in financial institutions represented in the language and speech culture of the population of the Lipetsk region. Based on 55 semi-structured interviews of three generations (centennials, millennials, elder generations) living in rural and urban settlements, issues of understanding and interpretation of financial institutions, features of trust, positive and negative experiences of interaction with various financial institutions were analyzed. The use of the constructivism made it possible to interpret (...) trust as an internal component of the practices of an agent involved in the current financial situation. The study showed that in regions with an average standard of living, an average level of financial culture and the dominance of a conservative model of financial behaviour, the difference between generations is less noticeable against the backdrop of a significant difference between residents of rural and urban settlements. The analysis of interviews with three generations of residents of the region showed that the conservative model of financial behaviour continues to be reproduced in the speech culture of the informants, where banks and insurance organizations remain the most trustworthy. The images of financial institutions, represented in the language of the interviews, revealed a high level of resentment associated with the experience of past events (the collapse of the USSR, privatization). The content analysis revealed the image of the state as a “collector of payments”, and to a lesser extent, a “helper” supporting a person in his relationship with financial institutions. (shrink)

This dissertation works out a new approach to understanding what makes a representation pictorial and what makes a representation imagistic. Over the last thirty years, the most common approach to these problems has been to claim that what makes a representation pictorial is that normal perceivers can perceive it in certain ways. By contrast, my approach singles out structural features of representational systems as that which distinguishes pictures from other kinds of representations. Pictorial systems are those that are transparent, (...) relatively syntactically sensitive, relatively replete, and semantically rich. All pictures are images, but the converse relation does not hold because images need not be transparent, though they satisfy the weaker condition of being mimetic. This approach is similar to, but enjoys advantages over, Nelson Goodman's work on the topic. ;The account of what makes a representation pictorial or imagistic is then brought to bear on the imagery debate, which concerns whether the brain implements imagistic systems of representation, specifically in the early stages of perception. A review of what we know about the workings of the visual and auditory systems reveals that no representations in the brain are pictorial, though some are imagistic in quite limited respects. Though they fail to be imagistic in many interesting respects, the early stages of the visual and auditory systems are highly isomorphic to what they represent. ;The role of isomorphism in perceptual states has been much discussed in both philosophy and cognitive neuroscience. The last two chapters of the dissertation argue that perceptual representations of traditionally secondary qualities like colors and sounds are isomorphic to those properties to a lesser degree than representations of traditionally primary qualities like shapes. This distinction in how such properties are represented can affect out intuitions concerning the nature of those properties and the nature of perceptual experience. Furthermore, it is argued that isomorphism is an important feature of perceptual representations because of the role it plays in making information cognitively available. This role for isomorphism is maintained even if one is an information theorist, and therefore thinks that lawful causal generalizations fix the content of representations. (shrink)

In this paper, I begin with an account of the initial distinction between likenesses and appearances, a distinction which may resemble the difference between sophists and philosophers. That distinction first arises immediately after the puzzling appearance of the noble sophist, who seems to occupy an odd space in between sophist and philosopher. In the second section, I look more closely at the noble sophist, and on what that figure might tell us about images and the use of images. I also (...) attempt to use the insights provided by the noble sophist in an investigation of the kind of images that Plato the author produces. This raises the question of the general notion of image as it appears in the Sophist, and especially of the dual nature of all images, which in turn invites reflection on certain features of the examination of being and non-being late in the dialogue. Finally, I return to the deception inherent in images, and I argue that this dialogue does not present the possibility of completely honest images. Nevertheless, I hope to show that some uses of deceptions and images are better than others. (shrink)

The article aims to concretize the phenomenological account concerning the problem of an auditory image. The author considers auditory imagery as a scientific object and compares different treatments of the problem to fix the potential and advantages of its phenomenological interpretation. In the first stage of the study, the author distinguishes the key characteristics of the image by means the lexical analysis. This is the perceptual (predominantly visual) nature of an image, integrality, and essentiality (image as (...) an idea). In the second stage, the understandings of the mental and auditory imagery in physiology, experimental psychology, music psychology, musicology, and interdisciplinary studies are described. In the third stage, the peculiar phenomenological ways of the comprehension of an auditory image are revealed. The phenomenological interest is to pick out consciousness which perceiving of an image equally from the process of perceiving and from entailing in an image. The specific phenomenological stance is placing an auditory image on the bound of transcendent (the process of perceiving) and immanent (an image that is already perceived). The auditory image is conceived as the unity of Modi of its givenness. Most fecks of this Modi are original, they cannot be transferred into other science scopes: they are the interconnection of all moments of the temporal unfolding, self-organization in the time, self-referentiality, non-semanticity, periodicity/randomness, eventuality, quasi-embodiment (physicality). Solely phenomenological problems are problems of the constitution of an auditory image, its life-horizon, intersubjectivity, and regional matching. The author infers that phenomenology does not conceive auditory image as sustained auditory representation, associated with acoustic memory. Its perceptual nature does not play a key role here. Moreover, the perceptual-semantic duality of the image is not fixed by the phenomenological description. The phenomenological approach is unique because it researches auditory data exhaustively but does not use semantic and referential analysis of them. The main feature of phenomenological description is the focus on the unity of auditory image: All the elements of auditory data are interpreted in their synthesis as the different levels of the unity of hearing image. Thus, the phenomenological approach as a whole is the most promising for comprehending such a dominant quality of the auditory image as integrality. (shrink)

My topic is a certain view about mental images: namely, the ‘Multiple Use Thesis’. On this view, at least some mental image-types, individuated in terms of the sum total of their representational content, are potentially multifunctional: a given mental image-type, individuated as indicated, can serve in a variety of imaginative-event-types. As such, the presence of an image is insufficient to individuate the content of those imagination-events in which it may feature. This picture is argued for, or (more (...) usually) just assumed to be true, by Christopher Peacocke, Michael Martin, Paul Noordhof, Bernard Williams, Alan White, and Tyler Burge. It is also presupposed by more recent authors on imagination such as Amy Kind, Peter Kung and Neil Van Leeuwen. I reject various arguments for the Multiple Use Thesis, and conclude that instead we should endorse SINGLE: a single image-type, individuated in terms of the sum total of its intrinsic representational content, can serve in only one imagination event-type, whose content coincides exactly with its own, and is wholly determined by it. Plausibility aside, the interest of this thesis is also in its iconoclasm, as well as the challenge it poses for the diverse theories that rest on the truth of the Multiple Use Thesis. (shrink)

Alain Badiou began the twenty-first century by considering the relationship between philosophy and notions of “the present.” In this period of his ongoing annual lecture series, the acclaimed philosopher took up the existential problem of how to be contemporary with one’s own time—that is, how to not simply inhabit a passing moment but bring a real present into existence. Images of the Present Time presents nearly three years of Badiou’s seminars, held from 2001 to 2004, partly against the backdrop of (...) the war in Iraq. Given while Badiou was writing Logics of Worlds, the second of the three volumes of Being and Event, these lectures address some of the same questions of existence in a particular world in a more personal and conversational tone, with reference to literature, philosophy, and contemporary politics and culture. He proposes a new concept of living in a real present as the twisting together of something from the past and something of the future. Featuring some of the philosopher’s most inspiring and approachable work, Images of the Present Time is an important book for all readers interested in the practical as well as conceptual possibilities of Badiou’s thought. (shrink)

Representational pictures and sculptures both present their objects visually: to grasp what they represent is in some sense to see, not only the representation before one, but the object represented. But is the form of visual presentation the same? Or does a deep difference lie at the heart of our experience of these representations, a difference in how each presents us with its object? Almost all philosophical discussion of pictures and 3D representations has assumed or implied a negative answer to (...) this question. The notable exception is M.G.F.Martin’s account of pictures in terms of an ‘image’, a pure visibile that presents the represented object and its features without exemplifying them. In order to interpret Martin’s view so as to bring out its plausibility, I relate it to the somewhat similar position advocated by Lambert Wiesing’s account of pictures and our experience of them. That done, I ask whether a position drawing on both these positions can justify drawing a fundamental distinction between the ways in which pictures and sculptures present what they represent. (shrink)