AuxTransUNet: Enhancing Remote Sensing Image Segmentation of Open-Pit Mining Areas in Qinghai–Tibet Plateau

AuxTransUNet: Enhancing Remote Sensing Image Segmentation of Open-Pit Mining Areas in Qinghai–Tibet Plateau

Accurate and efficient extraction of mining areas from remote sensing imagery is essential for resource investigation, environmental assessment, and ecological management. This task is particularly crucial for the intelligent analysis of large-scale mining landscapes, such as those found on the Qing...

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Bibliographic Details
Main Authors: Fangzhou Hong, Guojin He, Guizhou Wang, Zhaoming Zhang, Yan Peng
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)–transformer hybrid
land use mapping
open-pit mining
Qinghai–Tibet plateau
remote sensing
semantic segmentation
Online Access:https://ieeexplore.ieee.org/document/11112575/
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https://ieeexplore.ieee.org/document/11112575/

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