Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/1266
Title: Learning approaches in signal processing
Author(s): Chau, L.-P. (editor)
Wang, L. (editor)
Tan, T. (editor)
Editors: Siu, Wan Chi 
Issue Date: 2018
Publisher: Pan Stanford Publishing
Abstract: 
Coupled with machine learning, the use of signal processing techniques for big data analysis, Internet of things, smart cities, security, and bio-informatics applications has witnessed explosive growth. This has been made possible via fast algorithms on data, speech, image, and video processing with advanced GPU technology. This book presents an up-to-date tutorial and overview on learning technologies such as random forests, sparsity, and low-rank matrix estimation and cutting-edge visual/signal processing techniques, including face recognition, Kalman filtering, and multirate DSP. It discusses the applications that make use of deep learning, convolutional neural networks, random forests, etc. The applications include super-resolution imaging, fringe projection profilometry, human activities detection/capture, gesture recognition, spoken language processing, cooperative networks, bioinformatics, DNA, and healthcare.
URI: https://repository.cihe.edu.hk/jspui/handle/cihe/1266
CIHE Affiliated Publication: No
Appears in Collections:CIS Publication

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