I conceive of Spinoza’s substance monism as a response to Aristotle’s prohibition against actual infinity for one key reason: nature, being all things, is necessarily infi nite. Spinoza encapsulates his substance monism with the phrase, “Deus sive Natura,” implying that there is only one infinite substance, which also possesses an infi nity of attributes, of which we are but modes. These logical delineations of substance never actually break up God’s reality. Aristotle’s well-known argument against the reality of an actual infinity (...) in his Physics prohibits the existence of an actually infinite bodily substance because it would necessarily “destroy” (Physics 204b26-27) all other elements or bodies. On Aristotle’s view, there is a fundamental and concrete distinction between things: each substance is primarily a this (Categories 3b10). I maintain that Spinoza’s rationalism and radicalization of the principle of sufficient reason lends him greater explanatory potential than Aristotle to justify the (non) existence of actual infinity. (shrink)

St. John of the Cross was aware of the fact that his mysticism resisted prosaic, discursive representation; however, most contemporary scholars have overlooked this radical component of his work. First, I trace the major philosophical influences on John’s work: Medieval Neoplatonism and Scholasticism. Second, by drawing on the Barthesian-Foucauldian concept of the author function, I demonstrate that the Mystical Doctor saw his poetry as free-standing, inexhaustible by even his own efforts to systematize key aspects of his poetry—an insurmountable task, which (...) he had to be compelled to compile and publish by the nuns he guided in spiritual direction. (shrink)

I make the case that Spinoza built on Descartes’s conception of what it means for a mind to have an idea by linking it with his concept of expression because ideas express realities in terms of a causation‑conception conditional (but not vice versa). Briefly, if an idea is caused by a being, then that being is conceived through that idea. Descartes thinks of our clearly and distinctly possessing an idea as a sufficient ground for our expression of what we understand. (...) I take adequate ideas to be their equivalent. Spinoza links the connection and order of ideas with that of things because conceptualization of what is caused and its causes have to coincide (the causation‑conception conditional). Thus, Spinoza’s view must also involve clearly and distinctly possessing an idea as grounds for both expression of its content and the actual existence of a corresponding object of that idea. I stress the intentionality of ideas and discuss what follows from it taken alongside the univocity of being according to Spinoza’s substance monism. Put simply, on both Descartes’s and Spinoza’s views, ideas are always ideas of something. Ideas must express the reality of some corresponding being; in turn, being is itself expressive. (shrink)

I make the case that Spinoza built on Descartes’s conception of what it means for a mind to have an idea by linking it with his concept of expression because ideas express realities in terms of a causation‑conception conditional (but not vice versa). Briefly, if an idea is caused by a being, then that being is conceived through that idea. Descartes thinks of our clearly and distinctly possessing an idea as a sufficient ground for our expression of what we understand. (...) I take adequate ideas to be their equivalent. Spinoza links the connection and order of ideas with that of things because conceptualization of what is caused and its causes have to coincide (the causation‑conception conditional). Thus, Spinoza’s view must also involve clearly and distinctly possessing an idea as grounds for both expression of its content and the actual existence of a corresponding object of that idea. I stress the intentionality of ideas and discuss what follows from it taken alongside the univocity of being according to Spinoza’s substance monism. Put simply, on both Descartes’s and Spinoza’s views, ideas are always ideas of something. Ideas must express the reality of some corresponding being; in turn, being is itself expressive. (shrink)

This paper is a critique of Adorno’s ideas concerning jazz from his own perspective. I approach the topic from a dialectical standpoint, accounting for the historical development of jazz in the African-American context while trying to understand why Adorno found nothing of the genre redeemable; he scorned jazz as an unoriginal product of the culture industry. Drawing on the work of Eric Hobsbawm and Fumi Okiji on jazz, history, and Adorno, I try to demonstrate the internal contradiction of Adorno’s dislike (...) of jazz and appraisal of Beethoven. Although Adorno’s critical tools of the culture industry, deconcentration, and his usage of Lukács’s idea of reification are indispensable, Adorno should have consistently applied the subtle distinction between two intrinsically tied but nevertheless separate entities: an artwork and the mode of production in which it is developed. (shrink)

Data science, and the related field of big data, is an emerging discipline involving the analysis of data to solve problems and develop insights. This rapidly growing domain promises many benefits to both consumers and businesses. However, the use of big data analytics can also introduce many ethical concerns, stemming from, for example, the possible loss of privacy or the harming of a sub-category of the population via a classification algorithm. To help address these potential ethical challenges, this paper (...) maps and describes the main ethical themes that were identified via systematic literature review. It then identifies a possible structure to integrate these themes within a data science project, thus helping to provide some structure in the on-going debate with respect to the possible ethical situations that can arise when using data science analytics. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

Algorithms are probably the most sophisticated tools that men have had at their disposal since the beginnings of human history. They have transformed science, industry, society. They upset the concepts of work, property, government, private life, even humanity. Going easily from one extreme to the other, we rejoice that they make life easier for us, but fear that they will enslave us. To get beyond this vision of good vs evil, this book takes a new look at our time, the (...) Age of Algorithms. Creations of the human spirit, algorithms are what we made them. And they will be what we want them to be: it's up to us to choose the world we want to live in. (shrink)

We present a new and constructive proof of the Peter-Weyl theorem on the representations of compact groups. We use the Gelfand representation theorem for commutative C*-algebras to give a proof which may be seen as a direct generalization of Burnside's algorithm [3]. This algorithm computes the characters of a finite group. We use this proof as a basis for a constructive proof in the style of Bishop. In fact, the present theory of compact groups may be seen (...) as a natural continuation in the line of Bishop's work on locally compact, but Abelian, groups [2]. (shrink)

This chapter uncovers the complex negotiations for authority in various representations about futures of life which have been advanced by different branches of the sciences, and have culminated in the emerging concept of life as algorithm. It charts the historical shifts in expertise and representations of life, from naturalists, to mathematical modellers, and specialists in computation, and argues that physicists, game theorists, and economists now take a leading role in explaining and projecting futures of life. The chapter identifies Richard (...) Dawkins and Max Tegmark at the forefront of the concept of life as algorithm: the first inspired by game theory as a means to study evolution; the second proposing that a materialist basis of life could place humans and artificial intelligence on an equal footing. Through close reading of their respective texts, the chapter demonstrates that both thinkers consider life as an algorithm programmed to achieve success in survival and reproduction. (shrink)

In the present paper, I go beyond these examples by bringing into play an example that I nd more experimental in nature, namely that of the use of the so-called PSLQ algorithm in researching integer relations between numerical constants. It is the purpose of this paper to combine a historical presentation with a preliminary exploration of some philosophical aspects of the notion of experiment in experimental mathematics. This dual goal will be sought by analysing these aspects as they are (...) presented by some of the protagonists of the eld and discussing them using notions from contemporary philosophy of science. (shrink)

In this paper we present some algorithms for computing minimal conflicts. First of all we discuss the relationship between minimal conflicts and minimally inconsistent subsets. Then we introduce an algorithm for computing all minimally inconsistent subsets, which is applied to generating all minimal conflicts. Furthermore, an algorithm for computing all minimal conflicts using structured description is introduced, and its correctness is proved; its time complexity is also shown. The algorithm using structured description terminates in polynomial time for (...) some special system, such as the tree–structured systems. The algorithms are also complared with related works. (shrink)

In the article the basic procedures for finding of connective elements and resolving conflicts of references is analyzed. On the basis of this, a generalized algorithm is proposed that combines advantages of existing procedures for search for connective elements between phrases. The advantages of the selected procedures and their sequence are described, the formal description of input data and the results of the algorithm are presented. To optimize the procedure for scanning the text, the algorithm is performed (...) as an iterative reduction of the candidates for communication elements. This is achieved through the confirmation of non-conflict links and the gradual resolution of conflicts. (shrink)

Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.

“The forms of thought are first set out and stored in human language,” we read in the preface to the second edition of Hegel’s Science of Logic. Man thinks through language, and everything he “transforms into language and expresses in it contains a category, whether concealed, mixed, or well defined”. Language, then, harbors thought categories. There is a philosophy of language, but there is also a philosophy implied in language. How is this supposed to work? More specifically, how is this (...) supposed to work in Hegel’s own use of language?This paper is an attempt to give a simple answer to this question. There have been scholarly attempts to tie Hegel’s philosophy to his use of language.1 This paper... (shrink)

In a fluent, clear, and lively style this translation by two of Maslov's junior colleagues brings the work of the late Soviet scientist S. Yu. Maslov to a wider audience. Maslov was considered by his peers to be a man of genius who was making fundamental contributions in the fields of automatic theorem proving and computational logic. He published little, and those few papers were regarded as notoriously difficult. This book, however, was written for a broad audience of readers and (...) describes elegant examples of applications in such fields as computer science, artificial intelligence, operations research, economic modeling, and biological modeling, among others. The book also brings to light the work by the American mathematician E. L. Post, which inspired Maslov's own work in the development of a general theory and which has been long neglected by mathematicial logicians and systems theorists in the United States. The book's first chapter introduces the Rules of the Game. Part I, Mathematics of Calculi, covers E. L. Post's canonical systems, deductive systems and algorithms, and probabilistic calculi and deductive information. Part II, Horizonal Modeling, takes up a "toy" economy, the calculi of technological possibilities, and the development of rules. Part III, Vertical Modeling, deals with the topics of "to fight and to search" and the consequences of the asymmetry of cognitive mechanisms. Vladimir Lifschitz is affiliated with the Department of Computer Science at Stanford University, and Michael Gelfond with the Department of Electrical Engineering and Computer Science at the University of Texas, El Paso. Theory of Deductive Systems and Its Applicationsis included in the Foundation of Computing Series, edited by Michael Garey. (shrink)

This commentary on Daniel Stader's recent article, “Algorithms Don't Have a Future: On the Relation of Judgement and Calculation” develops and complicates his argument by suggesting that algorithms ossify multiple kinds of prejudices, namely, the structural prejudices of the programmer and the exemplary prejudices of the dataset. This typology at once suggests that the goal of transparency may be impossible, but this impossibility enriches the possibilities for developing Stader's concept of reflected prejudiced use.

It seems to be generally accepted that (a) counterfactual conditionals are to be analysed in terms of possible worlds and inter-world relations of similarity and (b) causation is conceptually prior to counterfactuals. I argue here that both (a) and (b) are false. The argument against (a) is not a general metaphysical or epistemological one but simply that, structurally speaking, possible worlds theories are wrong: this is revealed when we try to extend them to cover the case of probabilistic counterfactuals. Indeed (...) a type of counterfactual probability exists which cannot be expressed in possible worlds terms at all. The argument against (b) emerges when we look at the form of an adequate account of both probabilistic and non-probabilistic counterfactuals. I do this by sketching and defending an approach to counterfactuals that, first, invoke a generalized notion of cause as primitive and, secondly, is algorithmic in form: counterfactuals are evaluated algorithmically in terms of other counterfactuals, without vicious circularity. Structures like possible worlds do not play a role either in general truth-conditions or in evaluation. They are simply the wrong sorts of structures. (shrink)

Personal information is key to informational privacy and the algorithmically generated profiles of individuals. However, the concept of personal information and its nature is rarely discussed. The concept of personal information thus seems to be based on an idea of information as objective and truthful—as natural information—that is depicted as digital footprints in the online and digital realm. I argue that the concept of personal information should exit the realm of natural information and enter the realm of nonnatural information—grounded in (...) meaning, intention, and convention—as this will provide us with a concept that can account for potential misleadingness, inaccuracies, and mistakes. (shrink)

As algorithms pervade numerous facets of daily life, they are incorporated into systems for increasingly diverse purposes. These systems’ results are often interpreted differently by the designers who created them than by the lay persons who interact with them. This paper offers a proposal for human-centered algorithm design, which incorporates human and social interpretations into the design process for algorithmically based systems. It articulates three specific strategies for doing so: theoretical, participatory, and speculative. Drawing on the author’s work designing (...) and deploying multiple related systems, the paper provides a detailed example of using a theoretical approach. It also discusses findings pertinent to participatory and speculative design approaches. The paper addresses both strengths and challenges for each strategy in helping to center the process of designing algorithmically based systems around humans. (shrink)

Computability theory concerns information with a causal–typically algorithmic–structure. As such, it provides a schematic analysis of many naturally occurring situations. Emil Post was the first to focus on the close relationship between information, coded as real numbers, and its algorithmic infrastructure. Having characterised the close connection between the quantifier type of a real and the Turing jump operation, he looked for more subtle ways in which information entails a particular causal context. Specifically, he wanted to find simple relations on reals (...) which produced richness of local computability-theoretic structure. To this extent, he was not just interested in causal structure as an abstraction, but in the way in which this structure emerges in natural contexts. Post’s programme was the genesis of a more far reaching research project. In this article we will firstly review the history of Post’s programme, and look at two interesting developments of Post’s approach. The first of these developments concerns the extension of the core programme, initially restricted to the Turing structure of the computably enumerable sets of natural numbers, to the Ershov hierarchy of sets. The second looks at how new types of information coming from the recent growth of research into randomness, and the revealing of unexpected new computability-theoretic infrastructure. We will conclude by viewing Post’s programme from a more general perspective. We will look at how algorithmic structure does not just emerge mathematically from information, but how that emergent structure can model the emergence of very basic aspects of the real world. (shrink)

Significant research has been devoted to detecting people in images and videos. In this paper we describe a human de- tection method that augments widely used edge-based fea- tures with texture and color information, providing us with a much richer descriptor set. This augmentation results in an extremely high-dimensional feature space (more than 170,000 dimensions). In such high-dimensional spaces, classical machine learning algorithms such as SVMs are nearly intractable with respect to training. Furthermore, the number of training samples is much (...) smaller than the dimensionality of the feature space, by at least an order of magnitude. Finally, the extraction of features from a densely sampled grid structure leads to a high degree of multicollinearity. To circumvent these data characteristics, we employ Partial Least Squares (PLS) analysis, an effi- cient dimensionality reduction technique, one which pre- serves significant discriminative information, to project the data onto a much lower dimensional subspace (20 dimen- sions, reduced from the original 170,000). Our human de- tection system, employing PLS analysis over the enriched descriptor set, is shown to outperform state-of-the-art tech- niques on three varied datasets including the popular INRIA pedestrian dataset, the low-resolution gray-scale Daim- lerChrysler pedestrian dataset, and the ETHZ pedestrian dataset consisting of full-length videos of crowded scenes. (shrink)

Proceedings of the Steklov Institute of Mathematics is a cover-to-cover translation of the Trudy Matematicheskogo Instituta imeni V.A. Steklova of the Russian Academy of Sciences. Each issue ordinarily contains either one book-length article or a collection of articles pertaining to the same topic.

Purpose Algorithms are in the mainstream media news on an almost daily basis. Their context is invariably artificial intelligence and machine learning decision-making. In media articles, algorithms are described as powerful, autonomous actors that have a capability of producing actions that have consequences. Despite a tendency for deification, the prevailing critique of algorithms focuses on ethical concerns raised by decisions resulting from algorithmic processing. However, the purpose of this paper is to propose that the ethical concerns discussed are limited in (...) scope and suggest that it is not clear what concerns dominate the debate. Design/methodology/approach The paper uses a systematic mapping study approach to review articles appearing in leading UK national papers from the perspective of the ethical concerns over a period of one year. The articles are categorised using a widely cited framework detailing a taxonomy of ethical concerns. The UK context is important because of UK public policy initiatives around AI. Findings The research presented in this paper contributes the first systematic mapping study of articles appearing in leading UK national papers from the perspective of widely accepted ethical concerns such as inscrutable evidence, misguided evidence, unfair outcomes and transformative effects. Originality/value The research presented in this paper contributes the first systematic mapping study of articles appearing in leading UK national papers from the perspective of the ethical concerns. The UK context is important because of UK public policy initiatives around AI. To review the media content from the perspective of ethical concerns, this paper uses the synthesised conceptual map of ethical concerns developed by Mittelstad et al. Given the dominance of that framework, this paper’s contribution is also an important instantiation and experimental validation of using that conceptual map. (shrink)

In this paper, we propose a new concept named the uniform single valued neutrosophic graph. An illustrative example and some properties are examined. Next, we develop an algorithmic approach for computing the complement of the single valued neutrosophic graph. A numerical example is demonstrated for computing the complement of single valued neutrosophic graphs and uniform single valued neutrosophic graph.

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Scale Theory: A Nondisciplinary Inquiry by Joshua DiCaglioS. Scott GrahamScale Theory: A Nondisciplinary Inquiry. By Joshua DiCaglio. Minneapolis: University of Minnesota Press, 2021. 349 pp. Paperback: $30.00. ISBN: 978-1-5179-1207-9.Scale Theory embodies its title in every possible way. It offers both a deep dive into and a 10,000-foot view of scale, scalar thinking, and the role of scale in scientific inquiry. The subtitle, A Nondisciplinary Inquiry, is no less (...) apt. Author Joshua DiCaglio blends insights from rhetoric, philosophy, literary studies, and mysticism to create a novel account of scalar thinking. In so doing, he weaves together detailed thought experiments, the work of Gregory Bateson, and Philip K. Dick's account of an extraterrestrial communication he received while under the influence of anesthesia. Provocatively, Scale Theory treats these diverse intellectual resources as coequal contributors to an emerging theory of scale and scalar thinking. Within this nondisciplinary framework, the book is devoted to advancing two primary theses: (1) Notions of scale are undertheorized in science studies and related strands of new materialisms; and (2) Proper attention to questions of scale within these theoretical traditions should prompt a more thoughtful reconsideration of the merits of mystic holism. Ultimately, Scale Theory makes a compelling case for the first thesis and advances inquiry usefully in this area. With respect to the second thesis, DiCaglio refers to a certain academic "allergy" to holism (99), and I must confess I share this allergy. That said, I assume readers already predisposed favorably toward mystic holism are likely to find Scale Theory's attention to the second thesis thoughtful and engaging.Scale Theory is organized into three distinct parts. Part 1, "Algorithms for a Theory of Scale," presents three interrelated thought experiments that call upon readers to imagine themselves at various distances and vantage points with respect to several objects of interest. Part 1 is stylistically [End Page 388] Wittgensteinian. Like the Tractatus-Logico Philosophicus (Wittgenstein 2013) or Latour's "Irreductions," (1993), the thought experiments unfold as a series of numbered and nested propositions, each postulating or interrogating an emerging concept in DiCaglio's theory of scale. Part 2, "Configurations for a Theory of Scale," returns the reader to more familiar styles of prose, providing a sort of review of the relevant literature and its relationship to the insights of the thought experiments. Finally, part 3, "Rhetorical Technologies for a Theory of Scale," reflects on the twin marginalizations of rhetoric and mysticism in mainstream Western academia and argues for a new embrace of disembodied inquiry.The aforementioned thought experiments of part 1 outline DiCaglio's theories of scale, scalar thinking, and scalar analysis. The discussion makes extensive use of visual and cinematic metaphors to aid the reader's consideration of scalar questions. Ultimately, DiCaglio posits that scale is a function of the relationship between the "'being' of phenomena" and "the one who is measuring" (8). He argues, therefore, that "scale functions at a level above ontology and epistemology: scale is a means of orienting yourself both to experience and the being of things" (8). In making this argument, Scale Theory reflects on a range of scientific practices that require gradients of scale. Microscopy, telescopy, and simulations all provide scientists with tools to escape the mundane scales of embodied human experience. DiCaglio argues that "science must always find itself grouping things together, speaking of species, types, systems, and so on which exist on a different logical type than the individual encounters that make up these groups" (41). The taxonomic activities of scientific practice require shifts in scale to account for kingdoms, phyla, orders, genera, species, and all manner of nonbiological analogs.Within this framework, scale functions as a sort of meta-ontology that allows objects to be provisionally identified and delineated. Echoing Bateson, DiCaglio argues thatIn order for any thing to be said to exist whatsoever, a differential must exist out of which a difference can be discerned. Every differential occurs on some scale at which a fluctuation or movement is able to make a difference. If one goes to a smaller scale, any given differential is no longer able to be used to register a difference.(51... (shrink)

In cloud security, intrusion detection system (IDS) is one of the challenging research areas. In a cloud environment, security incidents such as denial of service, scanning, malware code injection, virus, worm, and password cracking are getting usual. These attacks surely affect the company and may develop a financial loss if not distinguished in time. Therefore, securing the cloud from these types of attack is very much needed. To discover the problem, this paper suggests a novel IDS established on a combination (...) of a leader-based k-means clustering (LKM), optimal fuzzy logic system. Here, at first, the input dataset is grouped into clusters with the use of LKM. Then, cluster data are afforded to the fuzzy logic system (FLS). Here, normal and abnormal data are inquired by the FLS, while FLS training is done by the grey wolf optimization algorithm through maximizing the rules. The clouds simulator and NSL-Knowledge Discovery and DataBase (KDD) Cup 99 dataset are applied to inquire about the suggested method. Precision, recall, and F-measure are conceived as evaluation criteria. The obtained results have denoted the superiority of the suggested method in comparison with other methods. (shrink)

Colonius suggests that, in using standard set theory as the language in which to express our computational-level theory of human memory, we would need to violate the axiom of foundation in order to express meaningful memory bindings in which a context is identical to an item in the list. We circumvent Colonius's objection by allowing that a list item may serve as a label for a context without being identical to that context. This debate serves to highlight the value of (...) specifying memory operations in set theoretic notation, as it would have been difficult if not impossible to formulate such an objection at the algorithmic level. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

The issue of whether formal reasoning or a computing-intensive approach is the most efficient manner to address scientific questions is the subject of some considerable debate and pertains not only to the nature of the phenomena and processes investigated by scientists, but also the nature of the equation and algorithm objects they use. Although algorithms and equations both rely on a common background of mathematical language and logic, they nevertheless possess some critical differences. They do not refer to the (...) same level of symbolization, as equations are based on integrated concepts in a denotational manner, while algorithms specifically break down a complex problem into more elementary operations, in an operational manner. They may therefore be considered as suited to the representation of different phenomena. Specifically, algorithms are by nature sufficient to represent weak emergent phenomena, but not strong emergent patterns, while equations can do both. Finally, the choice between equations and algorithms are by nature sufficient to represent weak emergent phenomena, but not strong emergent patterns, while equations behave conversely. We propose a simplified classification of scientific issues for which both equation- and/or algorithm-based approaches can be envisaged, and discuss their respective pros and cons. We further discuss the complementary and sometimes conflicting uses of equations and algorithms in a context of ecological theory of metapopulation dynamics. We finally propose both conceptual and practical guidelines for choosing between the alternative approaches. (shrink)

Nowadays, there has been an increase in security concerns regarding fingerprint biometrics. This problem arises due to technological advancements in bypassing and hacking methodologies. This has sparked the need for a more secure platform for identification. In this paper, we have used a deep Convolutional Neural Network as a pre-verification filter to filter out bad or malicious fingerprints. As deep learning allows the system to be more accurate at detecting and reducing false identification by training itself again and again with (...) test samples, the proposed method improves the security and accuracy by multiple folds. The implementation of a novel secure fingerprint verification platform that takes the optical image of a fingerprint as input is explained in this paper. The given input is pre-verified using Google’s pre-trained inception model for deep learning applications, and then passed through a minutia-based algorithm for user authentication. Then, the results are compared with existing models. (shrink)