Abstract
The water surface environment characterised by complexity and variability, is heavily influenced by weather. To address this problem, this paper proposes a water surface environment perception network based on the fusion of visual and positional information, and proposes an encoder-decoder based semantic segmentation neural network for classifying the pixel points of the input image into three categories: water, sky and environment (obstacles).
Original language | English |
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Title of host publication | Advanced Computational Intelligence and Intelligent Informatics - 8th International Workshop, IWACIII 2023, Proceedings |
Editors | Bin Xin, Naoyuki Kubota, Kewei Chen, Fangyan Dong |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 50-62 |
Number of pages | 13 |
ISBN (Print) | 9789819975891 |
DOIs | |
Publication status | Published - 2024 |
Event | 8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2023 - Beijing, China Duration: 3 Nov 2023 → 5 Nov 2023 |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 1931 CCIS |
ISSN (Print) | 1865-0929 |
ISSN (Electronic) | 1865-0937 |
Conference
Conference | 8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2023 |
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Country/Territory | China |
City | Beijing |
Period | 3/11/23 → 5/11/23 |
Keywords
- Attentional mechanisms
- Positional information
- Semantic segmentation
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Na, Q., Zuo, Z., Xu, N., Zhang, Z. Y., & Lu, Y. (2024). Research on Water Surface Environment Perception Method Based on Visual and Positional Information Fusion. In B. Xin, N. Kubota, K. Chen, & F. Dong (Eds.), Advanced Computational Intelligence and Intelligent Informatics - 8th International Workshop, IWACIII 2023, Proceedings (pp. 50-62). (Communications in Computer and Information Science; Vol. 1931 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-7590-7_5