Image approximation analysis system

Abstract

The invention discloses an image approximation analysis system, which is used in the field of intellectual property with specific image rules. The image approximation analysis system comprises a trained first deep learning module, a trained neural network data processing module, a combination learning unit and an approximation analysis unit. The trained first deep learning module receives an image to generate an initial map representation. The trained neural network data processing module receives graph specification information of an image under a specific image specification to generate a graph specification representation. The combination learning unit comprises a combination module and a trained second deep learning module. The combining module combines the initial graph representation with the graph specification representation to generate input information. The trained second deep learning module receives input information to generate a final graph representation. The approximation analysis unit compares the final image characterization with a reference image characterization of the reference image. Therefore, image specifications in the intellectual property field can be effectively incorporated, and the defect of image approximation degree comparison is overcome.

Description

technical field [0001] The present invention relates to an image approximation analysis system, in particular to an image approximation analysis system which utilizes deep learning to intelligently process image intellectual property data. Background technique [0002] In the face of international technological competition and impact, the development of intellectual property rights has become an extremely important part of industrial upgrading. With the wave of knowledge economy sweeping the world, the importance and value of intellectual property is beyond doubt, but with the emergence of new technologies, it will gradually lead to the future service direction of intellectual property. [0003] In the past, intellectual property rights required a lot of manpower to analyze from the perspectives of technology, law, and commercial interests, and then generate strategies and behaviors that are beneficial to the right holders. [0004] Among them, regarding the image-related p...

AI Technical Summary

Problems solved by technology

[0004] Among them, regarding the image-related parts of intellectual property rights, such as trademark images, copyright images, or design images, no matter whether it is searching and comparing previous cases, it is very labor-intensive, which directly affects the scope of rights, approval rate, and infringement. The possibility of being infringed, invalid or invalidated will cause significant profits and losses to the enterprise in terms of law and business

[0005] Therefore, it is necessary to use the artificial intelligence that is becoming more and more mature today to improve the problems of intellectual property rights such as labor-intensive, errors and disputes, and time-consuming and low efficiency.

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