Transformer-enhanced convolutional neural network with self-supervised learning for hyperspectral image classification

Yifan Sun; Bing Liu; Zhixiang Xue; Kuiliang Gao; Xibing Zuo; Mofan Dai

doi:10.1117/12.2667329

10 February 2023 Transformer-enhanced convolutional neural network with self-supervised learning for hyperspectral image classification

Yifan Sun, Bing Liu, Zhixiang Xue, Kuiliang Gao, Xibing Zuo, Mofan Dai

Author Affiliations +

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 1255238 (2023) https://doi.org/10.1117/12.2667329
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

In recent years, deep-learning-based hyperspectral image (HSI) processing and analysis have made significant progress. However, models with high performance require sufficient training samples because scarce labeled samples limit their generalization ability. To solve this problem, we adopt a self-supervised learning strategy and conduct self-training for a neural network model by obtaining different views of the same sample (positive pairs). As a result, the network can learn representative features for classification from unlabeled samples. In addition, to increase the spatial receptive field compared with the use of conventional convolutions, we use the transformer to capture long-distance dependencies for feature enhancement and adequately combine their advantages. Experimental results on two publicly available HSI datasets demonstrate that the proposed method can extract robust features through self-training on unlabeled samples and can be adapted to HSI classification tasks under the small sample conditions.

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Yifan Sun, Bing Liu, Zhixiang Xue, Kuiliang Gao, Xibing Zuo, and Mofan Dai "Transformer-enhanced convolutional neural network with self-supervised learning for hyperspectral image classification", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 1255238 (10 February 2023); https://doi.org/10.1117/12.2667329

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KEYWORDS

Feature extraction

Education and training

Transformers

Image classification

Convolutional neural networks

Hyperspectral imaging

Image processing

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