Triplet Attention Enhanced DeepLab V3+ for Semantic Segmentation: Improving Feature Extraction and Fine-Grained Understanding
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
Authors
- Yancong Deng (ORCID: https://orcid.org/0000-0001-7047-1164)
- Xiu Shu (ORCID: https://orcid.org/0000-0002-1205-9662)
- Zhuoran Li (ORCID: https://orcid.org/0000-0001-6281-2248)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.4108/eai.21-11-2024.2354635
- Primary Topic
- Advanced Neural Network Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00