Version 1
: Received: 14 October 2023 / Approved: 16 October 2023 / Online: 16 October 2023 (14:38:48 CEST)
How to cite:
Wu, D.; Su, B.; Hao, L.; Zhang, L.; Wang, Y.; Yan, Z. A Feature Extraction Network Based on Self-Attention Mechanism for Underwater Image. Preprints2023, 2023100974. https://doi.org/10.20944/preprints202310.0974.v1
Wu, D.; Su, B.; Hao, L.; Zhang, L.; Wang, Y.; Yan, Z. A Feature Extraction Network Based on Self-Attention Mechanism for Underwater Image. Preprints 2023, 2023100974. https://doi.org/10.20944/preprints202310.0974.v1
Wu, D.; Su, B.; Hao, L.; Zhang, L.; Wang, Y.; Yan, Z. A Feature Extraction Network Based on Self-Attention Mechanism for Underwater Image. Preprints2023, 2023100974. https://doi.org/10.20944/preprints202310.0974.v1
APA Style
Wu, D., Su, B., Hao, L., Zhang, L., Wang, Y., & Yan, Z. (2023). A Feature Extraction Network Based on Self-Attention Mechanism for Underwater Image. Preprints. https://doi.org/10.20944/preprints202310.0974.v1
Chicago/Turabian Style
Wu, D., Ye Wang and Zheping Yan. 2023 "A Feature Extraction Network Based on Self-Attention Mechanism for Underwater Image" Preprints. https://doi.org/10.20944/preprints202310.0974.v1
Abstract
Underwater image processing faces significant challenges due to the absorption and scattering of light as it travels through water. A self-supervised learning network based on the self-attention mechanism is proposed for underwater visual applications in this paper. The goal is to improve the effectiveness and stability of feature extraction from underwater images. By incorporating self-attention mechanism, the sensitivity of the original network architecture to degraded features of blurred underwater images is enhanced. The network proposed in this paper is trained using transfer learning and evaluated on various underwater image datasets. With distributive, quantitative, and qualitative advantages compared with other methods, experimental results have demonstrated that the algorithm presented shows a slighter decline in feature extraction ability for blurred images as the turbidity of water increases.
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
