Special Issue "Artificial Intelligence for Multimedia Signal Processing"
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 31 December 2020.
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Special Issue Editor
Prof. Dr. Byung-Gyu Kim Website
Department of IT Engineering, Sookmyung Women's University, Seoul, Korea
Interests: image/video signal processing; pattern recognition; computer vision; deep learning; artificial intelligence
Special Issue Information
At the ImageNet Large Scale Visual Re-Conversion Challenge (ILSVRC), a 2012 global image recognition contest, the University of Toronto Supervision team led by Prof. Geoffrey Hinton took first and second place by a landslide, sparking an explosion of interest in deep learning. Since then, global experts and companies such as Google, Microsoft, nVidia, and Intel have been competing to lead artificial intelligence technologies, such as deep learning. Now, they are developing deep-learning-based technologies applied to all industries and solving many classification and recognition problems.
These artificial intelligence technologies are also actively applied to broadcasting and multimedia processing technologies. A lot of research has been conducted in a wide variety of fields, such as content creation, transmission, and security, and these attempts have been made in the past two to three years to improve image, video, speech, and other data compression efficiency in areas related to MPEG media processing technology. Additionally, technologies such as media creation, processing, editing, and creating scenarios are very important areas of research in multimedia processing and engineering.
While this Special Issue invites topics broadly across advanced computational intelligence algorithms and technologies for emerging multimedia signal processing, some specific topics include but are not limited to:
- Signal/image/video processing algorithm for advanced deep learning;
- Fast and complexity reduction mechanism based on deep neural network;
- Protecting technologies for privacy/personalized media data;
- Advanced circuit/system design and analysis based on deep neural networks;
- Image/video-based recognition algorithm using deep neural network;
- Deep-learning-based speech and audio processing;
- Efficient multimedia sharing schemes using artificial intelligence;
- Artificial intelligence technologies for multimedia creation, processing, editing, and creating scenarios;
- Deep-learning-based web data mining and representation.