Applied Sciences: Advances of Computer Vision Call for Papers

CFP - Applied Sciences Special Issue on "Advances of Computer Vision"

Special Issue Information

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.

Guest Editors

Prof. Yuan-Kai Wang
Prof. Chin-Chuan Han
Prof. I-Cheng Chang

Deadline for manuscript submissions: 15 April 2020. 

Full details at: