Name
Title | ||
|---|---|---|
HSI-BERT: Hyperspectral Image Classification Using the Bidirectional Encoder Representation From Transformers |
Abstract | ||
|---|---|---|
Deep learning methods have been widely used in hyperspectral image classification and have achieved state-of-the-art performance. Nonetheless, the existing deep learning methods are restricted by a limited receptive field, inflexibility, and difficult generalization problems in hyperspectral image classification. To solve these problems, we propose HSI-BERT, where BERT stands for bidirectional encoder representations from transformers and HSI stands for hyperspectral imagery. The proposed HSI-BERT has a global receptive field that captures the global dependence among pixels regardless of their spatial distance. HSI-BERT is very flexible and enables the flexible and dynamic input regions. Furthermore, HSI-BERT has good generalization ability because the jointly trained HSI-BERT can be generalized from regions with different shapes without retraining. HSI-BERT is primarily built on a multihead self-attention (MHSA) mechanism in an MHSA layer. Moreover, several attentions are learned by different heads, and each head of the MHSA layer encodes the semantic context-aware representation to obtain discriminative features. Because all head-encoded features are merged, the resulting features exhibit spatial–spectral information that is essential for accurate pixel-level classification. Quantitative and qualitative results demonstrate that HSI-BERT outperforms any other CNN-based model in terms of both classification accuracy and computational time and achieves state-of-the-art performance on three widely used hyperspectral image data sets. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TGRS.2019.2934760 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Feature extraction,Bit error rate,Hyperspectral imaging,Shape,Deep learning,Kernel | Hyperspectral image classification,Computer vision,Encoder,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
58 | 1 | 0196-2892 |
Citations | PageRank | References |
2 | 0.36 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ji He | 1 | 2 | 0.36 |
| Lina Zhao | 2 | 2 | 1.37 |
| Hongwei Yang | 3 | 2 | 2.05 |
| Mengmeng Zhang | 4 | 115 | 24.91 |
| Wei Li | 5 | 1088 | 88.08 |