Coherent Spectral Feature Extraction Using Symmetric Autoencoders
Hyperspectral data acquired through remote sensing are invaluable for environmental and resource studies. While rich in spectral information, various complexities, such as environmental conditions, material properties, and sensor characteristics can cause significant variability even among pixels be...
Saved in:
| Main Authors: | Archisman Bhattacharjee, Pawan Bharadwaj |
|---|---|
| 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/10852302/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing feature learning of hyperspectral imaging using shallow autoencoder by adding parallel paths encoding
by: Bibi Noor Asmat, et al.
Published: (2025-05-01) -
A multi-domain dual-stream network for hyperspectral unmixing
by: Jiwei Hu, et al.
Published: (2024-12-01) -
Explainability Feature Bands Adaptive Selection for Hyperspectral Image Classification
by: Jirui Liu, et al.
Published: (2025-05-01) -
Autoencoder-Based Hyperspectral Unmixing with Simultaneous Number-of-Endmembers Estimation
by: Atheer Abdullah Alshahrani, et al.
Published: (2025-04-01) -
Detection of Bacterial Leaf Spot Disease in Sesame (<i>Sesamum indicum</i> L.) Using a U-Net Autoencoder
by: Minju Lee, et al.
Published: (2025-06-01)