Class-Imbalanced Graph Convolution Smoothing for Hyperspectral Image Classification
Author:
Affiliation:
1. School of Artificial Intelligence, Anhui University, Hefei, China
2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China
Funder
National Natural Science Foundation of China
Key Program of Natural Science Project of Educational Commission of Anhui Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/36/10354519/10457031.pdf?arnumber=10457031
Reference54 articles.
1. SpaSSA: Superpixelwise Adaptive SSA for Unsupervised Spatial-Spectral Feature Extraction in Hyperspectral Image
2. Dual-View Spectral and Global Spatial Feature Fusion Network for Hyperspectral Image Classification
3. More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification
4. MLR-DBPFN: A Multi-Scale Low Rank Deep Back Projection Fusion Network for Anti-Noise Hyperspectral and Multispectral Image Fusion
5. Tensor-Based Robust Principal Component Analysis With Locality Preserving Graph and Frontal Slice Sparsity for Hyperspectral Image Classification
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1. Pyramid Cascaded Convolutional Neural Network with Graph Convolution for Hyperspectral Image Classification;Remote Sensing;2024-08-11
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