U-Net for Remote Sensing: A Spectral Index-Based Approach with Explainable AI for Robust Change Detection

IF 8.6 1区地球科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Geoscience and Remote Sensing Pub Date : 2025-10-15 DOI:10.1109/tgrs.2025.3621733

Yosra Naceur, Sonia Bouzidi, Mariem Zaouali

引用次数: 0

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U-Net遥感：基于光谱指数的可解释人工智能鲁棒变化检测方法

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Geoscience and Remote Sensing 工程技术-地球化学与地球物理

CiteScore

11.50

自引率

28.00%

发文量

1912

审稿时长

4.0 months

期刊介绍： IEEE Transactions on Geoscience and Remote Sensing (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.