Advances of Computer Vision
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (15 April 2020) | Viewed by 4626
Special Issue Editors
Interests: intelligent video surveillance; face recognition; deep learning for object detection; robotic vision; embedded computer vision; sleep healthcare; neuromorphic computing
Special Issues, Collections and Topics in MDPI journals
Interests: computer vision; face recognition; video surveillance; hyperspectral image classification; content-based image retrieval; vision-based applications on embedded systems
Interests: image processing; computer vision; intelligent video surveillance; object detection and tracking; human pose estimation; 3D data acquisition technology; multimedia systems
Special Issue Information
Dear Colleagues,
Computer vision has become one of the most successful research topics in artificial intelligence. It is a key driving factor of successful applications such as face recognition, optical character recognition, biometrics, and video surveillance, which teach machines to see. Machines have eyes and brains to interpret the world by extracting meanings from image pixels. Recently, a vast development in various novel applications, including augmented reality, computational photography, autonomous vehicles, unmanned air vehicles and unmanned stores, egocentric vision, and three-dimensional movies, has brought computer vision to a new peak. In more real and complicated applications, machine learning and neural networks are employed to achieve a big leap in computer vision. Especially, deep learning shows great promises for computer vision applications.
Computer vision dramatically consumes processing power. However, thanks to the continuously increasing processing and sensing power of mobile processors and the quality of emerging displays, computer vision no longer requires an expensive specialized lab equipment and has proven its practical applicability in many domains like health, automotive, art, education, intelligent manufacturing, smart agriculture, and others. Embedded computer vision applies DSP processors, FPGA, and GPU devices to achieve edge computing. Moreover, neuromorphic computing, that is, the so-called next-level neural networks, can simulate the visual cortex and has great potential to develop high-performance computer vision algorithms.
In this Special Issue on “Advances in Computer Vision”, we invite authors to submit original research articles, reviews, and viewpoint articles related to recent advances at all levels of the applications and technologies of computer vision. We are particularly interested in presenting emerging technologies related to machine learning and deep learning that may have a significant impact on this research field. We are open to papers addressing a broad range of topics, from foundational topics regarding theoretical issues of computer vision to novel algorithms improving classical vision problems, advanced and technological systems for interesting applications, and innovative approaches in edge computing and neuromorphic computing. Topics of interest for this Special Issue include but are not limited to:
- Object detection, tracking, categorization, and recognition
- Machine learning and deep learning for computer vision
- Segmentation, feature extraction, and registration for images and videos
- Three-dimensional imaging, analysis, and applications
- Biometrics by the recognition of face, fingerprint, palm, iris and more
- Gesture, behavior, and event analysis for videos
- Computational photography, such as super-resolution, high-dynamic-range imaging, style transfer, colorization and decolorization, and more
- Beyond visual spectrum in computer vision, such as near-infrared and thermal image
- Embedded computer vision for edge computing
- Novel applications in video surveillance, augmented reality, sport video analysis, unmanned air vehicle, robotic vision, medical image, health care, AIoT, intelligent consumer electronics, and so on.
- Neuromorphic computing for computer vision.
Prof. Yuan-Kai Wang
Prof. Chin-Chuan Han
Prof. I-Cheng Chang
Guest Editors
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