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Conference Paper Edge Camera System Using Dee p Learning Method with Model Compression on Embedded Applications
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Authors
Yun Won Choi, Jang Woon Baek
Issue Date
2020-01
Citation
International Conference on Consumer Electronics (ICCE) 2020, pp.1-4
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICCE46568.2020.9043133
Abstract
This paper proposes an edge camera system using a compressed deep learning model for enhanced Video surveillance Management System of Smart City that analyzes existing recorded video. The proposed edge camera at the end terminal of the Video Surveillance Management System send the analyzed image, information and warning to the central system according to the situation analysis based on the information obtained by compressed deep learning for low memory and real-time operation in embedded system. We tested with edge camera installed in street lamp and confirmed stable operating performance and high recognition rate compared to existing system.
KSP Keywords
Camera system, Embedded applications, Learning methods, Management system, Model compression, Operating performance, Real-time operation, Recognition Rate, Smart city, deep learning(DL), embedded system