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Deep-Sea Organisms Tracking Using Dehazing and Deep Learning.

Authors :
Lu, Huimin
Uemura, Tomoki
Wang, Dong
Zhu, Jihua
Huang, Zi
Kim, Hyoungseop
Source :
Mobile Networks & Applications. Jun2020, Vol. 25 Issue 3, p1008-1015. 8p.
Publication Year :
2020

Abstract

Deep-sea organism automatic tracking has rarely been studied because of a lack of training data. However, it is extremely important for underwater robots to recognize and to predict the behavior of organisms. In this paper, we first develop a method for underwater real-time recognition and tracking of multi-objects, which we call "You Only Look Once: YOLO". This method provides us with a very fast and accurate tracker. At first, we remove the haze, which is caused by the turbidity of the water from a captured image. After that, we apply YOLO to allow recognition and tracking of marine organisms, which include shrimp, squid, crab and shark. The experiments demonstrate that our developed system shows satisfactory performance. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1383469X
Volume :
25
Issue :
3
Database :
Academic Search Index
Journal :
Mobile Networks & Applications
Publication Type :
Academic Journal
Accession number :
143520817
Full Text :
https://doi.org/10.1007/s11036-018-1117-9