In order to distinguish between computers and humans, CAPTCHA is widely used in links such as website login and registration. The traditional CAPTCHA recognition method has poor recognition ability and robustness to different types of verification codes. For this reason, the paper proposes a CAPTCHA recognition method based on convolutional neural network with focal loss function. This method improves the traditional VGG network structure and introduces the focal loss function to generate a new CAPTCHA recognition model. First, we perform preprocessing (...) such as grayscale, binarization, denoising, segmentation, and annotation and then use the Keras library to build a simple neural network model. In addition, we build a terminal end-to-end neural network model for recognition for complex CAPTCHA with high adhesion and more interference pixel. By testing the CNKI CAPTCHA, Zhengfang CAPTCHA, and randomly generated CAPTCHA, the experimental results show that the proposed method has a better recognition effect and robustness for three different datasets, and it has certain advantages compared with traditional deep learning methods. The recognition rate is 99%, 98.5%, and 97.84%, respectively. (shrink)

To evaluate the performance of rural land circulation mode through the analytic network hierarchy process, based on the results of the performance evaluation with analytic network process, we implemented efficiency analysis on five types of rural land circulation mode by two improved efficiency analytic procedures. Finally, we implemented sensitivity analysis for each criterion layer of the evaluation index system with the performance evaluation data, interpreted five types of rural land circulation mode from three perspectives including benefits, costs, and risks with (...) sensitivity analysis results, and drew related conclusions including higher revenue which will lead to smaller difficulty of the rural land circulation. Cost variables were negative variables of the selected rural land circulation mode, and higher risk would lead to the greater difficulty of rural land circulation and related conclusions. (shrink)