Deep Learning-Constructed Joint Transmission-Recognition for Internet of Things

The widely deployed Internet-of-Things (IoT) devices provide intelligent services with its cognition capability. Since the IoT data are usually transmitted to the server for recognition (e.g., image classification) due to low computational capability and limited power supply, achieving recognition a...

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Veröffentlicht in:	IEEE access 2019, Vol.7, p.76547-76561
Hauptverfasser:	Lee, Chia-Han, Lin, Jia-Wei, Chen, Po-Hao, Chang, Yu-Chieh
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Bandwidths Channel coding Cognition Complexity compressed sensing Computer architecture Deep learning deep neural networks Electronic devices Feature extraction Image classification Image compression Image transmission Internet of Things Internet of things (IoT) joint source-channel coding JPEG Machine learning Object recognition Performance evaluation recognition Servers Signal to noise ratio Training transfer learning transmission Wireless networks
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