Deep Learning-Based Computer Vision: Technologies and Applications

Dear Colleagues,

Whether based on machine learning or signal-processing methods, computer vision enables computers to process, analyze, and understand visual data from the world around us, improving its efficiency and accuracy in many applications. We can observe that computer vision has become increasingly important in a variety of fields, with uses in areas ranging from autonomous vehicles and surveillance systems to medical imaging and augmented reality. In recent years, deep learning has further revolutionized the field of computer vision, bringing about tremendous advances in many tasks and surpassing traditional computer vision techniques by generating state-of-the-art results. Therefore, studying the deep learning-based computer vision technologies and their applications is particularly important.

This Special Issue aims to present a comprehensive overview of the advances in deep learning for both low-level and high-level computer vision technologies and their applications. We believe that this Issue will be of interest to researchers who are working in the area of computer vision and deep learning.

We are pleased to invite you to present original high-quality research articles. In addition, review papers that overview the state-of-the-art in deep learning for computer vision and identify important research directions for the future are also welcome. Research areas may include (but are not limited to) the following: deep learning; computer vision; object detection; image classification; semantic segmentation; image generation; pose estimation; image reconstruction; image/video restoration; image/video enhancement; etc. We look forward to receiving your contributions.

Dr. Chao Ren
Dr. Yuanzhouhan Cao
Dr. Tao Li
Guest Editors

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