B-Xi / JSTARS_2020_DPN-HRA

Deep Prototypical Networks With Hybrid Residual Attention for Hyperspectral Image Classification, JSTARS, 2020

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Deep Prototypical Networks With Hybrid Residual Attention for Hyperspectral Image Classification, JSTARS, 2020

Bobo Xi, Jiaojiao Li, Yunsong Li, Rui song, Yanzi Shi, Songlin Liu and Qian Du.


Demo for the paper: Deep Prototypical Networks With Hybrid Residual Attention for Hyperspectral Image Classification.
(The complete project will be soon released after the related work is done)

Fig. 1: Architectures of our proposed DPN-HRA for HSI classification. HRA-based FE includes the parts of 1-D, 2-D, and 3-D FE. The RBAM and RSAM are integrally defined as the HRA module.

References

If you find this code helpful, please kindly cite:

[1]B. Xi, J. Li, Y. Li, R. Song, Y. Shi, S. Liu, Q. Du "Deep Prototypical Networks With Hybrid Residual Attention for Hyperspectral Image Classification," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 3683-3700, 2020, doi: 10.1109/JSTARS.2020.3004973.

[2] B. Xi, J. Li, Y. Li, R. Song, Y. Xiao, Q. Du, J. Chanussot, “Semisupervised Cross-scale Graph Prototypical Network for Hyperspectral Image Classification,” IEEE Transactions on Neural Networks and Learning Systems, pp. 1-15, 2022, doi: 10.1109/TNNLS.2022.3158280.

Citation Details

BibTeX entry:

@ARTICLE{Xi2020JSTARS,
  author={Xi, Bobo and Li, Jiaojiao and Li, Yunsong and Song, Rui and Shi, Yanzi and Liu, Songlin and Du, Qian},
  journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, 
  title={Deep Prototypical Networks With Hybrid Residual Attention for Hyperspectral Image Classification}, 
  year={2020},
  volume={13},
  number={},
  pages={3683-3700},
  doi={10.1109/JSTARS.2020.3004973}}
@ARTICLE{Xi_2022TNNLS_XGPN,
 author={Xi, Bobo and Li, Jiaojiao and Li, Yunsong and Song, Rui and Xiao, Yuchao and Du, Qian and Chanussot, Jocelyn},
 journal={IEEE Transactions on Neural Networks and Learning Systems}, 
 title={Semisupervised Cross-Scale Graph Prototypical Network for Hyperspectral Image Classification}, 
 year={2022},
 volume={},
 number={},
 pages={1-15},
 doi={10.1109/TNNLS.2022.3158280}}

Licensing

Copyright (C) 2020 Bobo Xi

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 3 of the License.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program.

About

Deep Prototypical Networks With Hybrid Residual Attention for Hyperspectral Image Classification, JSTARS, 2020

License:GNU General Public License v3.0


Languages

Language:Python 100.0%