Graph representation generation system, graph representation generation method and graph representation intelligent module thereof

Abstract

The invention discloses a graph representation generation system which is used in the field of intellectual property with specific image specifications. The graph representation generation system comprises a first deep learning module, a neural network data processing module and a combination learning unit. The first deep learning module is used for receiving an image to generate an initial image representation. The neural network data processing module is used for receiving graph specification information of an image under a specific image specification and generating graph specification representation according to the graph specification information. The combination learning unit comprises a combination module and a second deep learning module. The combining module is used for combining the initial graph representation and the graph specification representation to generate input information. The second deep learning module is used for receiving input information to generate a final graph representation. The invention also discloses a graph representation generation method and a graph representation intelligent module. Therefore, existing image specifications in the intellectual property field can be effectively incorporated, and the defect of image data processing in the intellectual property field is overcome.

Description

technical field [0001] The present invention relates to a graph representation generation system, a graph representation generation method and its graph representation intelligent module, in particular to a graph representation generation system that utilizes deep learning to intelligently process image intellectual property data, a graph representation generation method and its graph representation intelligent module. 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...

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.

Images