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Can I read FPA-Net: Frequency-Guided Position-Based Attention Network for Land Cover Image Segmentation on EtoBox?
FPA-Net: Frequency-Guided Position-Based Attention Network for Land Cover Image Segmentation by Al Shahriar Rubel; Frank Y. Shih is a Computer Science article available to read on EtoBox.
What is FPA-Net: Frequency-Guided Position-Based Attention Network for Land Cover Image Segmentation about?
Land cover segmentation has been a significant research area because of its multiple applications including the infrastructure development, forestry, agriculture, urban planning, and climate change research. In this paper, we propose a novel segmentation method, called Frequency-guided Position-based Attention Network (FPA-Net), for land cover image segmentation. Our method is based on encoder–decoder improved U-Net architecture with position-based attention mechanism and frequency-guided component. The position-based attention block is used to capture the spatial dependency among different feature maps and obtain the relationship among relevant patterns across the image. The frequency-guided component provides additional support with high-frequency features. Our model is simple and efficient in terms of time and space complexities. Experimental results on the Deep Globe, GID-15, and Land Cover AI datasets show that the proposed FPA-Net can achieve the best performance in both quantitative and qualitative measures as compared against other existing approaches.
Who reads FPA-Net: Frequency-Guided Position-Based Attention Network for Land Cover Image Segmentation?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Al Shahriar Rubel; Frank Y. Shih
- Publisher
- World Scientific Pub Co Pte Ltd
- Published
- 2023
- Language
- EN
- Field
- Computer Science (Physical Sciences)