Dual Fine-Grained network with frequency Transformer for change detection on remote sensing images
Change detection is a fundamental yet challenging task in remote sensing, crucial for monitoring urban expansion, land use changes, and environmental dynamics. However, compared with common color images, objects in remote sensing images exhibit minimal interclass variation and significant intraclass...
Saved in:
Main Authors: | Zhen Li, Zhenxin Zhang, Mengmeng Li, Liqiang Zhang, Xueli Peng, Rixing He, Leidong Shi |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-02-01
|
Series: | International Journal of Applied Earth Observations and Geoinformation |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225000408 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Principles of remote sensing : An introductory textbook /
by: Bakker WIm H ...[et al.]
Published: (2000) -
STFCropNet: A Spatiotemporal Fusion Network for Crop Classification in Multiresolution Remote Sensing Images
by: Wei Wu, et al.
Published: (2025-01-01) -
DeepGolf: A fine-grained perception framework for golf course distribution in the real world based on multi-source remote sensing data
by: Ning Li, et al.
Published: (2025-02-01) -
MLDFNet: A Multilabel Dual-Flow Network for Change Detection in Bitemporal Remote Sensing Images
by: Daniyaer Sidekejiang, et al.
Published: (2025-01-01) -
Rethinking the Key Factors for the Generalization of Remote Sensing Stereo Matching Networks
by: Liting Jiang, et al.
Published: (2025-01-01)