SOURCE-LINKED INTELLIGENCE
FSANet: Frequency-Spatial Aware Network for Image Segmentation
Image segmentation remains challenging due to occlusions, poor lighting, and irregular structures. Although transformer-based methods achieve high accuracy, they rely heavily on long-range spatial features, leading to high computational costs and neglecting prior knowledge or noise patterns, resulting in missing details and unclear boundaries. To address these issues, we propose Frequency Spatial Aware Network (FSANet), which integrates prior knowledge with a dual-domain solver to sequentially adapt to diverse segmentation tasks. Specifically, we design three key modules: (1) Structure Prior M
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T07:43:08.000Z
First collected: 2026-09-20T09:01:24.920Z. This is not the publication date.