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Binocular Vision of Fish Swarm Detection in Real-time Based on Deep Learning
- Source :
- OCEANS 2018 MTS/IEEE Charleston.
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- in the field of ocean development, fish swarm detection has significance for AUV’s autonomous navigation and fishing industry. Aim to present fish swarm detections are common based on $2D$ which lack of spatial information, has low accuracy and bad real-time performance, so we proposed systematic fish swarm detection and position method. We used deep learning target detection system to detect fish and used binocular vision position system to position, then fused every fish’s $3D$ information in camera vision to displayed fish swarm spatial information through radar map. Finally, the contrast experiment and is carried out to verify the effectiveness of the proposed method.
- Subjects :
- Computer science
business.industry
Deep learning
Feature extraction
Swarm behaviour
04 agricultural and veterinary sciences
02 engineering and technology
GeneralLiterature_MISCELLANEOUS
Object detection
law.invention
Fishing industry
law
040102 fisheries
0202 electrical engineering, electronic engineering, information engineering
0401 agriculture, forestry, and fisheries
020201 artificial intelligence & image processing
Computer vision
Artificial intelligence
Radar
business
Binocular vision
Spatial analysis
ComputingMethodologies_COMPUTERGRAPHICS
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- OCEANS 2018 MTS/IEEE Charleston
- Accession number :
- edsair.doi...........06433252c57e14630eeb490c09bb9a3d
- Full Text :
- https://doi.org/10.1109/oceans.2018.8604865