A Late-Stage Bitemporal Feature Fusion Network for Semantic Change Detection

Semantic change detection (SCD) is an important task in geoscience and Earth observation. By producing a semantic change map for each temporal phase, both the land use land cover (LULC) categories and change information can be interpreted. Recently some multitask learning-based SCD methods have been...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters 2025, Vol.22, p.1-5
Hauptverfasser:	Zhou, Chenyao, Zhang, Haotian, Guo, Han, Zou, Zhengxia, Shi, Zhenwei
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Aggregation Change detection Convolution Datasets Decoding Feature extraction feature fusion Land cover Land surface Land use Landsat Modules multitask learning Multitasking Remote sensing semantic change detection (SCD) Semantic segmentation Semantics Solid modeling
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