GLAFormer, a global-local attention Transformer with a cross-gated FFN, reports state-of-the-art change detection accuracy on three hyperspectral image datasets.
The regularized iteratively reweighted mad method for change detection in multi-and hyperspectral data,
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Global and Local Attention-Based Transformer for Hyperspectral Image Change Detection
GLAFormer, a global-local attention Transformer with a cross-gated FFN, reports state-of-the-art change detection accuracy on three hyperspectral image datasets.