Application forgery identification method and device based on computer vision, and electronic equipment

Abstract

The invention provides an application program counterfeiting identification method and device based on computer vision, and electronic equipment, and the method comprises the steps: obtaining a to-be-processed video of a picture of an application program operated by a user, carrying out the framing processing of the to-be-processed video, obtaining a plurality of video frames, importing each video frame into an identification model obtained through pre-training, carrying out the identification processing, and judging whether the application program operated by the user is counterfeited according to the identification result of the multiple video frames. According to the method, through a mode of pre-training the identification model, abnormity judgment can be carried out on the video frame containing the picture of the application program operated by the user, abnormity judgment can be rapidly and accurately carried out on the application program operated by the user through computer vision processing and the deep learning model, and on the basis of guaranteeing the judgment accuracy, time and labor cost are saved.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, in particular, to a method, device and electronic equipment for identifying fraudulent applications based on computer vision. Background technique [0002] Against the background of the vigorous development of the Internet, the integration of finance and the Internet has entered the era of Internet finance. Nowadays, Internet finance has shifted from a stage of rapid development to a stage of standardized development. With the in-depth development of special risk rectification work, the overall level of Internet financial risk is declining, the momentum of frequent occurrence of Internet financial risk cases has been initially curbed, industry regulatory rules and requirements have been further clarified, and the industry development environment has been further purified. [0003] For the user's judgment on the authenticity of financial applications, such as the authent...

AI Technical Summary

Problems solved by technology

In the existing processing methods, detection and judgment still need to rely on manual detection and judgment

This method involves a large amount of labor and time investment, and the efficiency of detection and judgment is very low

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