Li, Zhuoran and Shu, Xun and Deng, Yancong (2025) Triplet Attention Enhanced DeepLab V3+ for Semantic Segmentation: Improving Feature Extraction and Fine-Grained Understanding. In: Proceedings of the 2nd International Conference on Machine Learning and Automation, CONF-MLA 2024, November 21, 2024, Adana, Turkey.
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Abstract
Semantic segmentation is a critical task in computer vision that requires assigning class labels to individual pixels for a deeper understanding of visual scenes. This paper explores methods to enhance the DeepLab V3+ model by integrating attention mechanisms, specifically Triplet Attention and CBAM
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 18:27 |
| Last Modified: | 16 Apr 2026 21:38 |
| URI: | http://eprints.eai.eu/id/eprint/52546 |
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