Spatio-Temporal Feature Fusion and Guide Aggregation Network for Remote Sensing Change Detection

The field of remote sensing change detection (RSCD) has seen significant advancements recently, focusing on the precise identification and analysis of temporal changes in remote sensing images. Existing deep learning-based RSCD methods primarily rely on concatenation or subtraction to integrate feat...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2024, Vol.62, p.1-16
Hauptverfasser:	Wei, Hongguang, Wang, Nan, Liu, Yuan, Ma, Pengge, Pang, Dongdong, Sui, Xiubao, Chen, Qian
Format:	Artikel
Sprache:	eng
Schlagworte:	Aggregation Change detection Computation Convolution convolutional neural network (CNN) Convolutional neural networks Decoding Deep learning Detectors Feature extraction guide aggregation (GA) Image reconstruction Information processing Interference Modules Noise Object recognition Remote sensing Representations Semantics spatio-temporal feature fusion (STFF) Subtraction Temporal variations Transformers
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