Longshan Yang
Orcid: 0000-0002-3509-2123
  According to our database1,
  Longshan Yang
  authored at least 11 papers
  between 2016 and 2024.
  
  
Collaborative distances:
Collaborative distances:
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Bibliography
  2024
Hyperspectral Image Clustering by Superpixel- Based Low-Rank Constrained Bipartite Graph Learning.
    
  
    IEEE Geosci. Remote. Sens. Lett., 2024
    
  
TSANet: A deep learning framework for the delineation of agricultural fields utilizing satellite image time series.
    
  
    Comput. Electron. Agric., 2024
    
  
A spatio-temporal unmixing with heterogeneity model for the identification of remotely sensed MODIS aerosols: Exemplified by the case of Africa.
    
  
    Int. J. Appl. Earth Obs. Geoinformation, 2024
    
  
  2022
Semisupervised Hyperspectral Image Classification via Superpixel-Based Graph Regularization With Local and Nonlocal Features.
    
  
    IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
    
  
  2021
Glacier classification from Sentinel-2 imagery using spatial-spectral attention convolutional model.
    
  
    Int. J. Appl. Earth Obs. Geoinformation, 2021
    
  
  2020
Nonlocal Band-Weighted Iterative Spectral Mixture Model for Hyperspectral Imagery Denoising.
    
  
    IEEE Trans. Geosci. Remote. Sens., 2020
    
  
Combined Nonlocal Spatial Information and Spatial Group Sparsity in NMF for Hyperspectral Unmixing.
    
  
    IEEE Geosci. Remote. Sens. Lett., 2020
    
  
  2019
Multispectral Images Pan-Sharpening Based on Atrous Convolution Network and Deep Residual Network.
    
  
    Proceedings of the ICAIP 2019: 3rd International Conference on Advances in Image Processing, 2019
    
  
  2016
Denoising of hyperspectral imagery using an intrinsic spectral representation model with spatial smoothness constraint.
    
  
    Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016
    
  
Super-resolution reconstruction of hyperspectral imagery using an spectral unmixing based representational model.
    
  
    Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016
    
  
A novel unsupervised classification approach for hyperspectral imagery based on spectral mixture model and MARKOV random field.
    
  
    Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016