Advances in Signal Processing and Intelligent Recognition Systems [electronic resource] : Proceedings of Third International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2017), September 13-16, 2017, Manipal, India /
Contributor(s): Thampi, Sabu M [editor.] | Krishnan, Sri [editor.] | Corchado Rodriguez, Juan Manuel [editor.] | Das, Swagatam [editor.] | Wozniak, Michal [editor.] | Al-Jumeily, Dhiya [editor.] | SpringerLink (Online service).
Series: Advances in Intelligent Systems and Computing: 678Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XIV, 460 p. 264 illus. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319679341.Subject(s): EXTC Engineering
| Signal, Image and Speech Processing | Artificial IntelligenceDDC classification: 006.3 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
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Springer Nature eBookSummary: This Edited Volume gathers a selection of refereed and revised papers originally presented at the Third International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS’17), held on September 13–16, 2017 in Manipal, India. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. Taken together, they offer a valuable resource for all researchers and scientists engaged in the various fields of signal processing and related areas.
This Edited Volume gathers a selection of refereed and revised papers originally presented at the Third International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS’17), held on September 13–16, 2017 in Manipal, India. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. Taken together, they offer a valuable resource for all researchers and scientists engaged in the various fields of signal processing and related areas.
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