Remote sensing object detection (RSOD) requires compact backbones capable of preserving weak geometric cues under extreme scale variation and background clutter. Fixed structural operators provide complementary contour and frequency responses without introducing learnable operator coefficients. However, directly inject...
Wei Lu, Jun-Jie Li, Fei-Fei Sang et al.· 0 citations
Infrared small-target detection is widely used in early warning and remote monitoring. The targets are usually extremely weak, extremely small, and easily obscured by the chaotic background. However, existing methods still have poor detection accuracy in low-contrast and highly interfering scenarios, and many methods r...
Hao-Zhe Wang, Si-Bao Chen· Journal of Physics, Conferen...· 0 citations
Road extraction remains a challenging task due to irregular shapes, varying widths, occlusions, and complex terrain. Existing models often fail to address key issues, such as extraction interruptions caused by trees, buildings, or shadows, and the difficulty of distinguishing road edges from surrounding features under...
Weakly supervised change detection aims to identify land-cover changes from bi-temporal remote sensing images using limited annotations. However, relying solely on image-level supervision often leads to inaccurate change localization and noisy pseudo-labels. To address this issue, we propose an end-to-end framework for...
Die-Die Liu, Si-Bao Chen· Journal of Physics, Conferen...· 0 citations
Existing low-light enhancement methods often suffer from blur, noise, and inconsistent brightness, largely because they overlook frequency-domain characteristics. To address this, we propose the Multi-scale Dynamic Frequency-domain Optimization Network (MDFNet). Specifically, we introduce a Multi-Domain Attention Modul...
Yi-Fan Wang, Sibao Chen· International Conference on...· 0 citations
