Self-Supervised Learning With Multiscale Densely Connected Network for Hyperspectral Image Classification

Zhen Ye; Zhan Cao; Huan Liu; Haipeng Liu; Wei Li; Lin Bai; Xiaobo Li

doi:10.1109/tgrs.2024.3424394

ScienceGate Book Chapters

JOURNAL ARTICLE

Self-Supervised Learning With Multiscale Densely Connected Network for Hyperspectral Image Classification

Zhen Ye Zhan Cao Huan Liu Haipeng Liu Wei Li Lin Bai Xiaobo Li

Year: 2024 Journal: IEEE Transactions on Geoscience and Remote Sensing Vol: 62 Pages: 1-15 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tgrs.2024.3424394

Get Full-Text PDF Get Analytical Report

Keywords:

Hyperspectral imaging Computer science Artificial intelligence Pattern recognition (psychology) Remote sensing Contextual image classification Image (mathematics) Computer vision Geology

Metrics

Cited By

6.15

FWCI (Field Weighted Citation Impact)

Refs

0.94

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Remote-Sensing Image Classification

Physical Sciences → Engineering → Media Technology

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Self-Supervised Learning With Multiscale Densely Connected Network for Hyperspectral Image Classification

Metrics

Citation History

Topics

Related Documents

Multiscale Densely Connected Attention Network for Hyperspectral Image Classification

Densely Connected Multiscale Attention Network for Hyperspectral Image Classification

Hyperspectral image classification network based on multiscale supervised contrastive learning

Active deep densely connected convolutional network for hyperspectral image classification

Densely Connected Pyramidal Dilated Convolutional Network for Hyperspectral Image Classification