A Dual-Branches Multiscale Dynamic Partial Convolutional Attention Network for Remote Sensing Change Detection

Remote sensing change detection aims to accurately detect changes in buildings, roads, and other features in a pair of dual-temporal remote sensing images. In recent years, convolutional neural networks have achieved significant results in this task, but they lack the ability to model global feature...

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Bibliografske podrobnosti

Principais autores:	Wenbin Tang, Shuli Cheng, Anyu Du
Format:	Artigo
Jezik:	Inglês
Izdano:	IEEE 2025-01-01
Serija:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Teme:	Convolutional neural network (CNN) dynamic partial convolutional attention (DPCATT) multiscale context aggregation (MCA) parallel decoding aggregator (PDA) remote sensing change detection (RSCD)
Online dostop:	https://ieeexplore.ieee.org/document/10882914/
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