1. 2020
  2. Hyperspectral-Multispectral Image Fusion Enhancement Based on Deep Learning

    Yang, J., Zhao, Y. & Chan, J. C-W., 2020, Hyperspectral Image Analysis - Advances in Machine Learning and Signal Processing. Prasad, S. & Chanussot, J. (eds.). Springer, p. 407-433 (Advances in Computer Vision and Pattern Recognition).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  3. 2019
  4. Multi-Scale Wavelet 3D-CNN Based Hyperspectral Image Super-Resolution

    Yang, J., Zhao, Y., Chan, J. C-W. & Xiao, L., 2019, In : Remote Sensing. 11, 13, 1557.

    Research output: Contribution to journalArticle

  5. 2018
  6. Hyperspectral and Multispectral Image Fusion via Deep Two-Branches Convolutional Neural Network

    Yang, J., Zhao, Y. & Chan, J. C-W., 1 May 2018, In : Remote Sensing. 10, 5, 800.

    Research output: Contribution to journalArticle

  7. 2017
  8. Learning and Transferring Deep Joint Spectral-Spatial Features for Hyperspectral Classification

    Yang, J., Zhao, Y. & Chan, J. C-W., Aug 2017, In : IEEE Transactions on Geoscience and Remote Sensing. 55, 8, p. 4729-4742

    Research output: Contribution to journalArticle

  9. Joint Hyperspectral Super-Resolution and Unmixing with Interactive Feedback

    Yi, C., Zhao, Y., Yang, J., Chan, J. C-W. & Kong, S. G., Jul 2017, In : IEEE Transactions on Geoscience and Remote Sensing. 55, 7, p. 3823-3834 12 p., 7893730.

    Research output: Contribution to journalArticle

  10. No-Reference Hyperspectral Image Quality Assessment via Quality-Sensitive Features Learning

    Yang, J., Zhao, Y., Yi, C. & Chan, J. C-W., Apr 2017, In : Remote Sensing. 9, 4, 24 p., 305.

    Research output: Contribution to journalArticle

  11. 2016
  12. Hyperspectral image classification using two-channel deep convolutional neural network

    Yang, J., Zhao, Y., Chan, J. C-W. & Yi, C., 2016, IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, p. 5079-5082 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference paper

ID: 26875009