Multiscale Neighborhood Attention Transformer With Optimized Spatial Pattern for Hyperspectral Image Classification
Author:
Affiliation:
1. Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL, Canada
2. Department of Computer Science and Engineering, Alipurduar Government Engineering and Management College, Alipurduar, West Bengal, India
Funder
Natural Sciences and Engineering Research Council of Canada Discovery
Seed, Bridge and Multidisciplinary Fund from Memorial University of Newfoundland
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10248033.pdf?arnumber=10248033
Reference53 articles.
1. Hyperspectral Remote Sensing Image Classification Based on Rotation Forest
2. Semi-supervised classification of hyperspectral image using random forest algorithm
3. Region-Kernel-Based Support Vector Machines for Hyperspectral Image Classification
4. An effective feature selection method for hyperspectral image classification based on genetic algorithm and support vector machine
5. Spatial–Spectral ConvNeXt for Hyperspectral Image Classification
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3. A Dual-Branch Multiscale Transformer Network for Hyperspectral Image Classification;IEEE Transactions on Geoscience and Remote Sensing;2024
4. MSSFF: Advancing Hyperspectral Classification through Higher-Accuracy Multistage Spectral–Spatial Feature Fusion;Remote Sensing;2023-12-13
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