Deep Learning and Transformer Technologies for Image/Video Enhancement and Restoration
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 May 2024 | Viewed by 363
Special Issue Editors
Interests: image enhancement and restoration; computer vision; machine learning; deep neural networks
Special Issue Information
Dear Colleagues,
As we experience technological advancements like intelligent terminals, multimedia, and the internet, visual systems reliant on image/video data have been extensively applied across various industries. These include, but are not limited to, remote sensing mapping, security monitoring, and autonomous driving. However, in many real-world scenarios, image/video data generation and acquisition processes are susceptible to disruption, leading to considerable quality degradation. Therefore, image/video enhancement and restoration are critical processes in the computer vision field. In recent years, deep learning and Transformer technologies have emerged as solutions in computer vision, offering unprecedented improvements in image and video data quality. This Special Issue seeks original contributions that aim to advance the theory, architecture, and algorithmic design for deep learning, Transformer models in image/video enhancement and restoration, and novel applications of these technologies.
Dr. Xueyang Fu
Dr. Xiangyong Cao
Guest Editors
Manuscript Submission Information
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Keywords
- image/video enhancement
- denoising
- super-resolution
- deblurring
- dehazing
- inpainting
- deraining
- deep learning
- transformer
