Research Article
Coordinate Attention and Transformer Neck-Based Marine Organism Detection
@INPROCEEDINGS{10.1007/978-3-031-34899-0_3, author={Xiangjun Kong and Ning Wang and Tingkai Chen and Yanzheng Chen}, title={Coordinate Attention and Transformer Neck-Based Marine Organism Detection}, proceedings={Sensor Systems and Software. 13th EAI International Conference, S-Cube 2022, Dalian, China, December 7-9, 2022, Proceedings}, proceedings_a={S-CUBE}, year={2023}, month={6}, keywords={Marine organism detection Coordinate attention Swin transformer Model optimization}, doi={10.1007/978-3-031-34899-0_3} }- Xiangjun Kong
Ning Wang
Tingkai Chen
Yanzheng Chen
Year: 2023
Coordinate Attention and Transformer Neck-Based Marine Organism Detection
S-CUBE
Springer
DOI: 10.1007/978-3-031-34899-0_3
Abstract
Marine organism detection is crucial for the intelligent construction of open-sea farm. Suffering from low-contrast, color-deviation and detail-blurry underwater environment, a coordinate attention and transformer neck-based benthonic organism detection (CATNBOD) scheme has been devised. Main contributions are as follows: 1) The coordinate attention (CA) module is designed in the feature extraction network to obtain meaningful features, such that the small-scale benthonic organisms can be accurately detected. 2) To efficiently address the challenge derived from intra- and inter-class occlusions of benthonic organism, the rotation window-based swin transformer (ST) module is devised in the neck structure. Combining with CA and ST modules contributes to the proposed CATNBOD scheme. The effectiveness and superiority have been sufficiently demonstrated on publicly available UDD dataset.
