Learning Approaches in Signal Processing /
| Corporate Author: | |
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| Other Authors: | , , , |
| Format: | eBook |
| Language: | English |
| Published: |
Singapore :
Pan Stanford,
2018.
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| Series: | Pan Stanford series on Digital signal processing ;
vol. 2. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| 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 andcutting-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. |
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| Physical Description: | 1 online resource |
| ISBN: | 9780429061141 0429061145 9780429592263 0429592264 |