CG-FCLNet: Category-Guided Feature Collaborative Learning Network for Semantic Segmentation of Remote Sensing Images

Semantic segmentation of remote sensing images is a critical research area in the field of remote sensing. Despite the success of Convolutional Neural Networks (CNNs), they often fail to capture inter-layer feature relationsh... | Find, read and cite all the research you need on Tech Science Press

Authors

Publication Details

Journal
Computers, materials & continua/Computers, materials & continua (Print)
Published
2025-01-01
DOI
https://doi.org/10.32604/cmc.2025.060860
Citations
2
Primary Topic
Remote-Sensing Image Classification
Type
article
Field-Weighted Citation Impact
2.27

Funders

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article

CG-FCLNet: Category-Guided Feature Collaborative Learning Network for Semantic Segmentation of Remote Sensing Images

Min Yao, Y. H. Zhang, Guoqiang Hu
2 citations
Computers, materials & continua/Computers, materials & continua (Print)
Remote-Sensing Image Classification
2.27
article

CG-FCLNet: Category-Guided Feature Collaborative Learning Network for Semantic Segmentation of Remote Sensing Images

Min Yao, Y. H. Zhang, Guoqiang Hu
article en
2 citations

Abstract

Semantic segmentation of remote sensing images is a critical research area in the field of remote sensing. Despite the success of Convolutional Neural Networks (CNNs), they often fail to capture inter-layer feature relationsh... | Find, read and cite all the research you need on Tech Science Press

Computers, materials & continua/Computers, materials & continua (Print)Vol. 83(2)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Remote-Sensing Image Classification
2.27
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