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

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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Bibliographic Details
Main Authors: Wenbin Tang, Shuli Cheng, Anyu Du
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
dynamic partial convolutional attention (DPCATT)
multiscale context aggregation (MCA)
parallel decoding aggregator (PDA)
remote sensing change detection (RSCD)
Online Access:https://ieeexplore.ieee.org/document/10882914/
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