Sheng Lin
Orcid: 0000-0002-1096-3973Affiliations:
- Xidian University, School of Aerospace Science and Technology, Xi'an, China
According to our database1,
Sheng Lin
authored at least 15 papers
between 2020 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Hyperspectral Anomaly Detection via Low-Rank Representation with Dual Graph Regularizations and Adaptive Dictionary.
Remote. Sens., June, 2024
Dynamic Low-Rank and Sparse Priors Constrained Deep Autoencoders for Hyperspectral Anomaly Detection.
IEEE Trans. Instrum. Meas., 2024
Low-Rank and Sparse Representation Inspired Interpretable Network for Hyperspectral Anomaly Detection.
IEEE Trans. Instrum. Meas., 2024
IEEE Trans. Instrum. Meas., 2024
IEEE Trans. Instrum. Meas., 2024
Memory-Augmented Autoencoder With Adaptive Reconstruction and Sample Attribution Mining for Hyperspectral Anomaly Detection.
IEEE Trans. Geosci. Remote. Sens., 2024
2023
Hyperspectral Anomaly Detection Using Spatial-Spectral-Based Union Dictionary and Improved Saliency Weight.
Remote. Sens., July, 2023
Frontiers Comput. Neurosci., February, 2023
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023
Dual Collaborative Constraints Regularized Low-Rank and Sparse Representation via Robust Dictionaries Construction for Hyperspectral Anomaly Detection.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023
Hyperspectral Anomaly Detection via Sparse Representation and Collaborative Representation.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023
Two-Stream Isolation Forest Based on Deep Features for Hyperspectral Anomaly Detection.
IEEE Geosci. Remote. Sens. Lett., 2023
2022
Hyperspectral Anomaly Detection via Dual Dictionaries Construction Guided by Two-Stage Complementary Decision.
Remote. Sens., 2022
Multiscale Superpixel Guided Discriminative Forest for Hyperspectral Anomaly Detection.
Remote. Sens., 2022
2020
Object Detection in Remote Sensing Images Based on Improved Bounding Box Regression and Multi-Level Features Fusion.
Remote. Sens., 2020