HLSK-CASMamba: hybrid large selective kernel and convolutional additive self-attention mamba for hyperspectral image classification
Abstract Classifying hyperspectral images (HSIs) is a key challenge in remote sensing, with convolutional neural networks (CNNs) and transformer models becoming leading techniques in this area. CNNs, while effective, often struggle to adequately capture intricate semantic features, and increasing ne...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44443-025-00060-z |
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