EXNet: (2+1)D Extreme Xception Net for Hyperspectral Image Classification
3-D CNNs have demonstrated their capability to capture intricate nonlinear relationships within hyperspectral images (HSIs). However, the computational complexity of 3-D CNNs often leads to slower processing speeds, limited generalization, and susceptibility to overfitting. In response to these chal...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10423094/ |