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Main Authors: Yu, Zihan, Li, Tianxiao, Zhu, Yuxin, Pan, Rongze
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.07824
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author Yu, Zihan
Li, Tianxiao
Zhu, Yuxin
Pan, Rongze
author_facet Yu, Zihan
Li, Tianxiao
Zhu, Yuxin
Pan, Rongze
contents Change detection, as an important and widely applied technique in the field of remote sensing, aims to analyze changes in surface areas over time and has broad applications in areas such as environmental monitoring, urban development, and land use analysis.In recent years, deep learning, especially the development of foundation models, has provided more powerful solutions for feature extraction and data fusion, effectively addressing these complexities. This paper systematically reviews the latest advancements in the field of change detection, with a focus on the application of foundation models in remote sensing tasks.
format Preprint
id arxiv_https___arxiv_org_abs_2410_07824
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Exploring Foundation Models in Remote Sensing Image Change Detection: A Comprehensive Survey
Yu, Zihan
Li, Tianxiao
Zhu, Yuxin
Pan, Rongze
Computer Vision and Pattern Recognition
Change detection, as an important and widely applied technique in the field of remote sensing, aims to analyze changes in surface areas over time and has broad applications in areas such as environmental monitoring, urban development, and land use analysis.In recent years, deep learning, especially the development of foundation models, has provided more powerful solutions for feature extraction and data fusion, effectively addressing these complexities. This paper systematically reviews the latest advancements in the field of change detection, with a focus on the application of foundation models in remote sensing tasks.
title Exploring Foundation Models in Remote Sensing Image Change Detection: A Comprehensive Survey
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2410.07824