mlsanityData to 7 Oct 2026

Single-source Domain Expansion Network for Cross-Scene Hyperspectral Image Classification

arXiv 2209.01634 ↗First posted 4 Sep 2022cs.CVcited by 25

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Abstract (arXiv)

Currently, cross-scene hyperspectral image (HSI) classification has drawn increasing attention. It is necessary to train a model only on source domain (SD) and directly transferring the model to target domain (TD), when TD needs to be processed in real time and cannot be reused for training. Based on the idea of domain generalization, a Single-source Domain Expansion Network (SDEnet) is developed to ensure the reliability and effectiveness of domain extension. The method uses generative adversarial learning to train in SD and test in TD. A generator including semantic encoder and morph encoder is designed to generate the extended domain (ED) based on encoder-randomization-decoder architecture, where spatial and spectral randomization are specifically used to generate variable spatial and spectral information, and the morphological knowledge is implicitly applied as domain invariant information during domain expansion. Furthermore, the supervised contrastive learning is employed in the discriminator to learn class-wise domain invariant representation, which drives intra-class samples of SD and ED. Meanwhile, adversarial training is designed to optimize the generator to drive intra-class samples of SD and ED to be separated. Extensive experiments on two public HSI datasets and one additional multispectral image (MSI) dataset demonstrate the superiority of the proposed method when compared with state-of-the-art techniques.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 31 of its 52 references that are in the map. First posted on arXiv 4 Sep 2022.

Builds on

31 of 52 references.

References · 31

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Citing papers per year: 2022: 2; 2023: 7; 2024: 8; 2025: 8.

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  1. 2023Parameter-Efficient Transfer Learning for Remote Sensing Image-Text Retrievalcited by 24
  2. 2022Language-aware Domain Generalization Network for Cross-Scene Hyperspectral Image Classificationcited by 20
  3. 2024Single Domain Generalization for Crowd Countingcited by 17
  4. 2024Enhancing Information Maximization with Distance-Aware Contrastive Learning for Source-Free Cross-Domain Few-Shot Learningcited by 13
  5. 2023Domain-adaptive Message Passing Graph Neural Networkcited by 10
  6. 2022One-Class Risk Estimation for One-Class Hyperspectral Image Classificationcited by 6
  7. 2023FactoFormer: Factorized Hyperspectral Transformers with Self-Supervised Pretrainingcited by 6
  8. 2024Remote Sensing Image Segmentation Using Vision Mamba and Multi-Scale Multi-Frequency Feature Fusioncited by 6
  9. 2025Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classificationcited by 6
  10. 2025SpectralX: Parameter-efficient Domain Generalization for Spectral Remote Sensing Foundation Modelscited by 5
  11. 2023INSURE: An Information Theory Inspired Disentanglement and Purification Model for Domain Generalizationcited by 4
  12. 2025Cross-domain Hyperspectral Image Classification based on Bi-directional Domain Adaptationcited by 4
13 more
  1. 2023GraSS: Contrastive Learning with Gradient Guided Sampling Strategy for Remote Sensing Image Semantic Segmentationcited by 3
  2. 2024FViT: A Focal Vision Transformer with Gabor Filtercited by 3
  3. 2024Dual adversarial and contrastive network for single-source domain generalization in fault diagnosiscited by 3
  4. 2024Multisource Collaborative Domain Generalization for Cross-Scene Remote Sensing Image Classificationcited by 3
  5. 2025Deep Learning Based Domain Adaptation Methods in Remote Sensing: A Comprehensive Surveycited by 2
  6. 2023A Non-Uniform Low-Light Image Enhancement Method with Multi-Scale Attention Transformer and Luminance Consistency Losscited by 1
  7. 2024Unsupervised Few-Shot Continual Learning for Remote Sensing Image Scene Classificationcited by 1
  8. 2024C3DG: Conditional Domain Generalization for Hyperspectral Imagery Classification with Convergence and Constrained-risk Theoriescited by 1
  9. 2025FedX: Explanation-Guided Pruning for Communication-Efficient Federated Learning in Remote Sensingcited by 1
  10. 2023Multi-view learning for automatic classification of multi-wavelength auroral imagescited by 0
  11. 2025HOpenCls: Training Hyperspectral Image Open-Set Classifiers in Their Living Environmentscited by 0
  12. 2025From Pixels to Images: A Structural Survey of Deep Learning Paradigms in Remote Sensing Image Semantic Segmentationcited by 0
  13. 2025Automatic Extraction of Road Networks by using Teacher-Student Adaptive Structural Deep Belief Network and Its Application to Landslide Disastercited by 0