Research on Image Processing and Recognition Algorithms in Software Information Systems Based on Deep Learning

With the rapid development of deep learning technology, its application in image processing and recognition has become a hot research topic. The application of these technologies in software information systems such as automatic image classification, facial recognition, and medical image analysis not only improves processing efficiency but also enhances recognition accuracy. This article focuses on the training and deployment of adversarial generative network models in deep learning algorithms for graphic processing and recognition applications. Finally, two sets of simulation experiments were conducted, and the results are as follows: in the face recognition system, the recognition accuracy optimized by the deep learning algorithm based on adversarial generative networks improved by an average of 8.9% compared to traditional methods. In the traffic sign recognition system, the overall average recall index improved by 12.45%. This article proposes an improved network architecture and training strategy, which significantly improves the quality of image generation and the accuracy of recognition models in software information systems.