Marine Organism Detection and Classification from Underwater Vision Based on the Deep CNN Method
Joint Authors
Han, Fenglei
Yao, Jingzheng
Zhu, Haitao
Wang, Chunhui
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-25
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Seabed fishing depends on humans in common, for instance, the sea cucumber, sea urchin, and scallop fishing, which is always a very dangerous task.
Considering the underwater complex environment conditions such as low temperature, dim vision, and high pressure, collecting the marine products using underwater robots is commonly regarded as a feasible solution.
The key technique of the underwater robot development is to detect and locate the main target from underwater vision.
This research is based on the deep convolutional neural network (CNN) to realize the target recognition from underwater vision.
The RPN (Region Proposal Network) is used to optimize the feature extraction capability.
Deep learning dataset is prepared using an underwater video obtained from a sea cucumber fishing ROV (Remote Operated Vehicle).
The inspiration of the network structure and the improvements come from the Faster RCNN and Hypernet method, and for the underwater dataset, the method proposed in this paper shows a good performance of recall and object detection accuracy.
The detection runs with a speed of 17 fps on a GPU, which is applicable to be used for real-time processing.
American Psychological Association (APA)
Han, Fenglei& Yao, Jingzheng& Zhu, Haitao& Wang, Chunhui. 2020. Marine Organism Detection and Classification from Underwater Vision Based on the Deep CNN Method. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1194759
Modern Language Association (MLA)
Han, Fenglei…[et al.]. Marine Organism Detection and Classification from Underwater Vision Based on the Deep CNN Method. Mathematical Problems in Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1194759
American Medical Association (AMA)
Han, Fenglei& Yao, Jingzheng& Zhu, Haitao& Wang, Chunhui. Marine Organism Detection and Classification from Underwater Vision Based on the Deep CNN Method. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1194759
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194759