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
Experiments across two datasets show that NBASNet outperforms existing methods across all evaluation metrics, and visualizations further verify its effectiveness and reliability in addressing the aforementioned challenges.
An end-to-end framework for weakly supervised change detection is proposed that effectively improves weakly supervised change detection performance and introduces a Reliability-Aware Contrastive Learning strategy to enhance the separability of change representations.
Die-Die Liu, Si-Bao Chen· Journal of Physics, Conferen...· 0 citations
This work introduces a Multi-Domain Attention Module (MDAM) to integrate spatial features with frequency-domain global context, and a Dynamic Frequency-domain Fusion Module (DFFM) that employs dynamic filters for detail refinement, noise suppression, and local brightness correction.
Yi-Fan Wang, Si-Bao Chen· International Conference on...· 0 citations
