STeInFormer: Spatial–Temporal Interaction Transformer Architecture for Remote Sensing Change Detection
Convolutional neural networks and attention mechanisms have greatly benefited remote sensing change detection (RSCD) because of their outstanding discriminative ability. Existent RSCD methods often follow a paradigm of using a noninteractive Siamese neural network for multitemporal feature extractio...
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Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10815617/ |
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