High-resolution remote sensing change detection must distinguish genuine changes from pseudo-changes caused by misregistration, illumination, and texture variations. We propose STDFNet, a lightweight Symmetric Temporal Difference and Multi-Scale Context Gating Network. A shared MobileNetV2 extracts four-level bi-tempor...
Chong-Yi Huang, Jia-Shuo Li, Pan-Rong Chen et al.· 2026 2nd International Confe...· 0 citations
Remote sensing change detection requires accurate localization of changes in high-resolution bi-temporal imagery while maintaining a compact computational footprint. Existing lightweight methods often rely on simple absolute differencing and progressive upsampling, which may lead to pseudo-changes, blurred boundaries,...
Yu-Wei Han, Zhi-Yuan Su, Jia-Shuo Li et al.· 2026 2nd International Confe...· 0 citations
Remote sensing building change detection is critical for urban monitoring and disaster assessment, yet existing deep learning methods suffer from three limitations: the heavy computational cost of Transformer models, the information loss induced by naive differencing, and the tendency of convex gating to degenerate int...
Yi-Gui Huang, Shu-Zhao Li, Gui-Li Li et al.· 2026 2nd International Confe...· 0 citations
Remote sensing change detection (RSCD) aims to identify land-cover changes from bitemporal images and is widely used in urban monitoring, disaster assessment, and land-resource analysis. Lightweight RSCD models usually rely on compact backbones and efficient temporal interaction, but most of them update bitemporal feat...
Chaoyun Mai, Hai-Peng He, Hao Xie et al.· IEEE Journal of Selected Top...· 0 citations
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