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 learni 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 efficiency and quality of image processing, but also promotes the accuracy and speed of medical diagno development of deep learning and GPU optimi mate-rial. If material is not included in statutory regulation orexceeds the permitted use, you will need Vol.5, Issue 01, June, 2024 , Li2, Huixiang Li3, Yadong Shi4, Xiaoan Zhan Computer Business Information Computer Shanghai,China Electrical New York University, NY, USA E-mail:lihuixiang95@gmail.com ABSTRACT learning models, especially in the rocessing matching, and fusion. This convergence not only improves the diagnosis, and looks forward to the future application and optimization in various industries.
Loading....