GPU-Optimized Image Processing and Generation Based on Deep Learning and Computer Vision

Abstract

In recent years, deep learning has become a core technology in many fields such as computer vision. The parallel processing capability of GPU, greatly accelerates the training and inference of deep learning models, especially in the field of image processing and generation. This paper discusses the cooperation and differences between deep learning and traditional computer vision technology and focuses on the significant advantages of GPU in medical image processing applications such as image reconstruction, filter enhancement, image registration, matching, and fusion. This convergence not only improves the efficiency and quality of image processing, but also promotes the accuracy and speed of medical diagnosis, and looks forward to the future application and development of deep learning and GPU optimization in various industries.