publications

2023

1. TAI

   Contrastive-enhanced Domain Generalization with Federated Learning

   Xinhui Yu, Dan Wang, Martin McKeown, and Z. Jane Wang

   IEEE Transactions on Artificial Intelligence, 2023

2022

1. GRSL

   Cross-Domain Few-Shot Contrastive Learning for Hyperspectral Images Classification

   Suhua Zhang, Zhikui Chen, Dan Wang, and Z. Jane Wang

   IEEE Geoscience and Remote Sensing Letters, 2022
2. TIM

   Transformer-Based End-to-End Anatomical and Functional Image Fusion

   Jing Zhang, Aiping Liu, Dan Wang, Yu Liu, Z. Jane Wang, and 1 more author

   2022

   Bib HTML

   @article{9864213,
     author = {Zhang, Jing and Liu, Aiping and Wang, Dan and Liu, Yu and Wang, Z. Jane and Chen, Xun},
     title = {Transformer-Based End-to-End Anatomical and Functional Image Fusion},
     volume = {34},
     year = {2022},
     doi = {10.1109/TIM.2022.3200426},
     html = https://ieeexplore.ieee.org/abstract/document/9864213,
   }

2021

1. TIP

   Interpreting Bottom-Up Decision-Making of CNNs via Hierarchical Inference

   Dan Wang, Xinrui Cui, Xun Chen, Rabab Ward, and Z. Jane Wang

   IEEE Transactions on Image Processing, 2021

   Bib HTML

   @article{9491931,
     author = {Wang, Dan and Cui, Xinrui and Chen, Xun and Ward, Rabab and Wang, Z. Jane},
     journal = {IEEE Transactions on Image Processing},
     title = {Interpreting Bottom-Up Decision-Making of CNNs via Hierarchical Inference},
     volume = {30},
     year = {2021},
     pages = {6701-6714},
     doi = {10.1109/TIP.2021.3097187},
     html = https://ieeexplore.ieee.org/abstract/document/9491931,
   }

2. ICCV

   Multi-View 3D Reconstruction With Transformers

   Dan Wang, Xinrui Cui, Xun Chen, Zhengxia Zou, Tianyang Shi, and 3 more authors

   In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), Oct 2021

   Bib HTML

   @inproceedings{Wang_2021_ICCV,
     author = {Wang, Dan and Cui, Xinrui and Chen, Xun and Zou, Zhengxia and Shi, Tianyang and Salcudean, Septimiu and Wang, Z. Jane and Ward, Rabab},
     title = {Multi-View 3D Reconstruction With Transformers},
     booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
     volume = {12},
     month = oct,
     year = {2021},
     pages = {5722-5731},
     html = https://openaccess.thecvf.com/content/iccv2021/html/wang_multi-view_3d_reconstruction_with_transformers_iccv_2021_paper.html,
   }

2020

1. TMM

   Feature-Flow Interpretation of Deep Convolutional Neural Networks

   Xinrui Cui, Dan Wang, and Z. Jane Wang

   IEEE Transactions on Multimedia, Oct 2020

   Bib HTML

   @article{9019647,
     author = {Cui, Xinrui and Wang, Dan and Wang, Z. Jane},
     journal = {IEEE Transactions on Multimedia},
     title = {Feature-Flow Interpretation of Deep Convolutional Neural Networks},
     year = {2020},
     volume = {22},
     number = {7},
     pages = {1847-1861},
     doi = {10.1109/TMM.2020.2976985},
     html = https://ieeexplore.ieee.org/abstract/document/9019647,
   }

2. TNNLS

   CHIP: Channel-Wise Disentangled Interpretation of Deep Convolutional Neural Networks

   Xinrui Cui*, Dan Wang*, and Z. Jane Wang

   IEEE Transactions on Neural Networks and Learning Systems, Oct 2020

   Bib HTML

   @article{8924894,
     author = {Cui*, Xinrui and Wang*, Dan and Wang, Z. Jane},
     journal = {IEEE Transactions on Neural Networks and Learning Systems},
     title = {CHIP: Channel-Wise Disentangled Interpretation of Deep Convolutional Neural Networks},
     year = {2020},
     volume = {31},
     number = {10},
     pages = {4143-4156},
     doi = {10.1109/TNNLS.2019.2952322},
     html = https://ieeexplore.ieee.org/abstract/document/8924894,
   }

2019

1. TMM

   Multi-Scale Interpretation Model for Convolutional Neural Networks: Building Trust Based on Hierarchical Interpretation

   Xinrui Cui, Dan Wang, and Z. Jane Wang

   IEEE Transactions on Multimedia, Oct 2019

   Bib HTML

   @article{8653995,
     author = {Cui, Xinrui and Wang, Dan and Wang, Z. Jane},
     journal = {IEEE Transactions on Multimedia},
     title = {Multi-Scale Interpretation Model for Convolutional Neural Networks: Building Trust Based on Hierarchical Interpretation},
     year = {2019},
     volume = {21},
     number = {9},
     pages = {2263-2276},
     doi = {10.1109/TMM.2019.2902099},
     html = https://ieeexplore.ieee.org/abstract/document/8653995,
   }

2018

1. TGRS

   Robust Sparse Unmixing for Hyperspectral Imagery

   Dan Wang, Zhenwei Shi, and Xinrui Cui

   IEEE Transactions on Geoscience and Remote Sensing, Oct 2018

   Bib HTML

   @article{8082740,
     author = {Wang, Dan and Shi, Zhenwei and Cui, Xinrui},
     journal = {IEEE Transactions on Geoscience and Remote Sensing},
     title = {Robust Sparse Unmixing for Hyperspectral Imagery},
     year = {2018},
     volume = {56},
     number = {3},
     pages = {1348-1359},
     doi = {10.1109/TGRS.2017.2761912},
     html = https://ieeexplore.ieee.org/abstract/document/8082740,
   }

2017

1. IJRS

   Multi-feature Sea–land Segmentation based on Pixel-wise Learning for Optical Remote-sensing Imagery

   Dan Wang, Xinrui Cui, Fengying Xie, Zhiguo Jiang, and Zhenwei Shi

   International Journal of Remote Sensing, Oct 2017

   Bib HTML

   @article{sea-land,
     author = {Wang, Dan and Cui, Xinrui and Xie, Fengying and Jiang, Zhiguo and Shi, Zhenwei},
     journal = {International Journal of Remote Sensing},
     title = {Multi-feature Sea–land Segmentation based on Pixel-wise Learning for Optical Remote-sensing Imagery},
     year = {2017},
     volume = {38},
     number = {15},
     pages = {4327-4347},
     html = https://www.tandfonline.com/doi/citedby/10.1080/01431161.2017.1317938,
   }

2016

1. IGARSS

   Collaborative sparse unmixing of hyperspectral data using L2,P norm

   Dan Wang, Zhenwei Shi, and Wei Tang

   In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Oct 2016

   Bib HTML

   @inproceedings{7730820,
     title = {Collaborative sparse unmixing of hyperspectral data using L2,P norm},
     author = {Wang, Dan and Shi, Zhenwei and Tang, Wei},
     booktitle = {2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)},
     year = {2016},
     volume = {},
     number = {},
     pages = {6978-6981},
     doi = {10.1109/IGARSS.2016.7730820},
     html = https://ieeexplore.ieee.org/abstract/document/7730820,
   }