Deep learning model for real-time image compression in Internet of Underwater Things (IoUT)

Recently, the advancements of Internet-of-Things (IoT) have expanded its application in underwater environment which leads to the development of a new field of Internet of Underwater Things (IoUT). It offers a broader view of applications such as atmosphere observation, habitat monitoring of sea ani...

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Veröffentlicht in:	Journal of real-time image processing Jg. 17; H. 6; S. 2097 - 2111
Hauptverfasser:	Krishnaraj, N., Elhoseny, Mohamed, Thenmozhi, M., Selim, Mahmoud M., Shankar, K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2020 Springer Nature B.V
Schlagworte:	Algorithms Artificial neural networks Coding standards Communication Computer Graphics Computer Science Data compression Data transmission Deep learning Discrete Wavelet Transform Energy efficiency Image coding Image compression Image Processing and Computer Vision Image quality Image reconstruction Image transmission Internet of Things Machine learning Multimedia Information Systems Neural networks Pattern Recognition Propagation Sensors Signal to noise ratio Signal,Image and Speech Processing Special Issue Paper Underwater Deep learning Image compression Image reconstruction IoUT Underwater
ISSN:	1861-8200, 1861-8219
Online-Zugang:	Volltext
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