From Data to Knowledge: A Knowledge Graph-Guided Framework to Deep Learning for Hyperspectral Image Classification
Recent advances in deep learning have significantly improved hyperspectral image (HSI) classification. However, deep learning models for HSI classification typically rely on one-hot labels, which lack semantic information and fail to reflect relationships between land cover classes, leading to subop...
Saved in:
| Main Authors: | Runmin Lei, Yuchuan Zhou, Zixuan Wang, Xiang Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11029574/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multiscale Graph Transformer Network With Dynamic Superpixel Pyramid for Hyperspectral Image Classification
by: Tingting Wang, et al.
Published: (2025-01-01) -
Spatial-Spectral Contrastive Graph Neural Network for Few-Shot Hyperspectral Image Classification
by: Zhaoxia Xue, et al.
Published: (2025-01-01) -
Hyperspectral Band Selection via Heterogeneous Graph Convolutional Self-Representation Network
by: Junde Chen, et al.
Published: (2025-01-01) -
Global–Local Multigranularity Transformer for Hyperspectral Image Classification
by: Zhe Meng, et al.
Published: (2025-01-01) -
Curriculum Preview and Review Based on Knowledge Distillation for Hyperspectral Image Classification
by: Wen Xie, et al.
Published: (2025-01-01)