Hyperspectral Classification Using Deep Belief Networks Based on Conjugate Gradient Update and Pixel-Centric Spectral Block Features
This article describes the use of deep belief networks (DBNs) based on the conjugate gradient (CG) update algorithm for hyperspectral classification. DBNs perform two processes: unsupervised pretraining and supervised fine-tuning. The parameter update method in the fine-tuning stage plays a key role...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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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/9139188/ |