@article{Feng2025,
author = {},
journal = {Optics and Lasers in Engineering},
title = {Physics-guided Super-resolutionCompressed Encoding Spectral Imaging System},
year = {2024 (Under Review)},
published = {0}
}@article{Chen2024MajorRevision,
author = {},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Hierarchical Multi-Granularity Ship Classification Using Hierarchical Constrastive Learning with Learnable Class Quires},
year = {2024 (Major Revision)},
published = {0}
}@article{Xiong2024MajorRevision,
author = {},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Spatial-Spectral-Temporal Correlation Filter for Hyperspectral Object Tracking},
year = {2024 (Major Revision)},
published = {0}
}@article{Li2024UnderReview,
author = {},
journal = {Pattern Recognition},
title = {Towards Universal Representation Learning for Multi-domain Hyperspectral Object Tracking},
year = {2024 (Under Review)},
published = {0}
}@article{Zhao2024MajorRevision,
author = {},
journal = {Optics Express},
title = {Self-supervised constrained super-resolution fast coded spectral imaging system},
year = {2024 (Major Revision)},
published = {0}
}@article{10381757,
author = {Xiong, Fengchao and Li, Tianhan and Chen, Jingzhou and Zhou, Jun and Qian, Yuntao},
journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title = {Mask-Guided Local–Global Attentive Network for Change Detection in Remote Sensing Images},
year = {2024},
pages = {3366-3378},
volume = {17},
doi = {10.1109/JSTARS.2024.3350044},
keywords = {Feature extraction;Transformers;Remote sensing;Task analysis;Semantics;Memory management;Interference;Attention mechanism;change detection (CD);change mask;convolutional neural network (CNN);remote sensing image}
}@article{10379170,
author = {Ye, Minchao and Chen, Junbin and Xiong, Fengchao and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Adaptive Graph Modeling With Self-Training for Heterogeneous Cross-Scene Hyperspectral Image Classification},
year = {2024},
pages = {1-15},
volume = {62},
doi = {10.1109/TGRS.2023.3348953},
keywords = {Transfer learning;Adaptation models;Semantics;Correlation;Training;Sensors;Noise measurement;Adaptive graph modeling (AGM);cross-scene classification;heterogeneous transfer learning;hyperspectral image (HSI);self-training (ST)}
}@article{10463066,
author = {Fu, Guanyiman and Xiong, Fengchao and Lu, Jianfeng and Zhou, Jun and Zhou, Jiantao and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Hyperspectral Image Denoising via Spatial–Spectral Recurrent Transformer},
year = {2024},
pages = {1-14},
volume = {62},
doi = {10.1109/TGRS.2024.3374953},
keywords = {Noise reduction;Correlation;Three-dimensional displays;Current transformers;Feature extraction;Convolution;Hyperspectral imaging;Deep learning;global spectral correlation (GSC);hyperspectral image (HSI) denoising;nonlocal spatial self-similarity (NSS);transformer}
}@inproceedings{Zhang2024,
author = {},
booktitle = {IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium},
title = {Semantic-Aware Alignment Network for Cross-resolution Change Detection},
year = {2024},
pages = {5455-5458},
doi = {10.1109/IGARSS52108.2023.10282593},
keywords = {Wavelet transforms;Frequency-domain analysis;Semantics;Neural networks;Sensors;Remote sensing;Change detection;remote sensing image;Discrete Wavelet Transform;convolutional neural network}
}@article{10438474,
author = {Li, Zhuanfeng and Xiong, Fengchao and Zhou, Jun and Lu, Jianfeng and Zhao, Zhuang and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Material-Guided Multiview Fusion Network for Hyperspectral Object Tracking},
year = {2024},
pages = {1-15},
volume = {62},
doi = {10.1109/TGRS.2024.3366536},
keywords = {Feature extraction;Hyperspectral imaging;Target tracking;Videos;Object tracking;Visualization;Spatial resolution;Hyperspectral object tracking;hyperspectral unmixing;multihead attention;multiview fusion}
}@article{Ye2024,
author = {Ye, Jin and Xiong, Fengchao and Zhou, Jun and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Iterative Low-Rank Network for Hyperspectral Image Denoising},
year = {2024},
pages = {1-15},
volume = {62},
doi = {10.1109/TGRS.2024.3449130}
}@article{Feng2024,
author = {},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {A Transformer-Based CrossDomain Few-Shot Learning Method for Hyperspectral Target Detection},
year = {2024}
}@article{Ye2024a,
author = {Ye, Minchao and Ling, Jiawei and Xiong, Fengchao and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Discriminative Vision Transformer for Heterogeneous Cross-Domain Hyperspectral Image Classification},
year = {2024}
}@article{Fu2024,
author = {Fu, Guanyiman and Xiong, Fengchao and Lu, Jianfeng and Zhou, Jun},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image Denoising},
year = {2024},
pages = {1-14},
volume = {62},
doi = {10.1109/TGRS.2024.3446812}
}@article{10675432,
author = {Hu, Di and Yuan, Xia and Xi, Huiying and Li, Jie and Song, Zhenbo and Xiong, Fengchao and Zhang, Kai and Zhao, Chunxia},
journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title = {Road Structure Inspired UGV-Satellite Cross-View Geo-Localization},
year = {2024},
pages = {16767-16786},
volume = {17},
doi = {10.1109/JSTARS.2024.3457756}
}@article{Xiong2024,
author = {Xiong, Fengchao and Li, Tianhan and Yang, Yi and Zhou, Jun and Lu, Jianfeng and Qian, Yuntao},
journal = {IEEE Trans. Geosci. Remote Sens.},
title = {Wavelet Siamese Network with Semi-supervised Domain Adaptation for Remote Sensing Image Change Detection},
year = {2024},
pages = {1-1},
doi = {10.1109/TGRS.2024.3432819},
keywords = {Change detection;remote sensing image;frequency domain analysis;domain adaptation}
}@article{Feng2023,
author = {Feng, Shou and Feng, Rui and Liu, Jianfei and Zhao, Chunhui and Xiong, Fengchao and Zhang, Lifu},
journal = {IEEE Geoscience and Remote Sensing Letters},
title = {An Attention-Based Multiscale Spectral–Spatial Network for Hyperspectral Target Detection},
year = {2023},
pages = {1-5},
volume = {20},
doi = {10.1109/LGRS.2023.3265938},
keywords = {Feature extraction;Convolutional neural networks;Testing;Detectors;Training;Transformers;Object detection;Hyperspectral images (HSIs);Siamese structure;target detection;vision Transformer (ViT)}
}@article{10198268,
author = {Xiong, Fengchao and Zhou, Jiantao and Zhou, Jun and Lu, Jianfeng and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Multitask Sparse Representation Model-Inspired Network for Hyperspectral Image Denoising},
year = {2023},
pages = {1-15},
volume = {61},
doi = {10.1109/TGRS.2023.3300542},
keywords = {Noise reduction;Correlation;Feature extraction;Optimization;Redundancy;Dictionaries;Computational modeling;Deep unfolding;hyperspectral image (HSI) denoising;multitask learning;sparse representation (SR)}
}@article{10128966,
author = {Li, Zhuanfeng and Xiong, Fengchao and Zhou, Jun and Lu, Jianfeng and Qian, Yuntao},
journal = {IEEE Transactions on Image Processing},
title = {Learning a Deep Ensemble Network With Band Importance for Hyperspectral Object Tracking},
year = {2023},
pages = {2901-2914},
volume = {32},
doi = {10.1109/TIP.2023.3263109},
keywords = {Hyperspectral imaging;Target tracking;Object tracking;Visualization;Feature extraction;Task analysis;Videos;Object tracking;hyperspectral videos;learning to optimize;ensemble learning}
}@inproceedings{10219765,
author = {Xiong, Fengchao and Zhou, Jun and Zhao, Zhuang and Qian, Yuntao},
booktitle = {2023 IEEE International Conference on Multimedia and Expo (ICME)},
title = {Iterative Refinement Network for Hyperspectral Image Denoising},
year = {2023},
pages = {2753-2758},
doi = {10.1109/ICME55011.2023.00468},
keywords = {Knowledge engineering;Noise reduction;Estimation;Iterative methods;Noise measurement;Task analysis;Hyperspectral imaging;Hyperspectral image denoising;deep learning;iterative refinement}
}@inproceedings{10283365,
author = {Xiong, Fengchao and Gu, Zhongyi and Zheng, Wenbin and Li, Tianhan and Zhou, Jun},
booktitle = {IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium},
title = {Multi-Task Attentional U-Net for Hyperspectral Image Denoising},
year = {2023},
pages = {7336-7339},
doi = {10.1109/IGARSS52108.2023.10283365},
keywords = {Correlation;Noise reduction;Geoscience and remote sensing;Multitasking;Calibration;Usability;Hyperspectral imaging}
}@inproceedings{10430600,
author = {Jin, Yuheng and Ye, Minchao and Xiong, Fengchao and Qian, Yuntao},
booktitle = {2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
title = {Cross-Domain Heterogeneous Hyperspectral Image Classification Based on Meta-Learning with Task-Adaptive Loss Function},
year = {2023},
pages = {1-5},
doi = {10.1109/WHISPERS61460.2023.10430600},
keywords = {Metalearning;Adaptation models;Signal processing algorithms;Classification algorithms;Task analysis;Optimization;Hyperspectral imaging;Hyperspectral image;cross-domain classification;meta-learning}
}@article{10258356,
author = {Xiong, Fengchao and Zhou, Jun and Zhou, Jiantao and Lu, Jianfeng and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Deep Parameterized Neural Networks for Hyperspectral Image Denoising},
year = {2023},
pages = {1-15},
volume = {61},
doi = {10.1109/TGRS.2023.3318001},
keywords = {Noise reduction;Training;Noise measurement;Neural networks;Image reconstruction;Convolutional neural networks;Computational modeling;Convolutional neural networks;hyperspectral image (HSI) denoising;learning to optimize (L2O);sparse representation (SR)}
}@inproceedings{10282593,
author = {Li, Tianhan and Xiong, Fengchao and Zheng, Wenbin and Li, Zhuanfeng and Zhou, Jun and Qian, Yuntao},
booktitle = {IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium},
title = {Wavelet Siamese Network for Change Detection in Remote Sensing Images},
year = {2023},
pages = {5455-5458},
doi = {10.1109/IGARSS52108.2023.10282593},
keywords = {Wavelet transforms;Frequency-domain analysis;Semantics;Neural networks;Sensors;Remote sensing;Change detection;remote sensing image;Discrete Wavelet Transform;convolutional neural network}
}@article{https://doi.org/10.1049/cvi2.12238,
author = {Ye, Minchao and Wang, Chenglong and Meng, Zhihao and Xiong, Fengchao and Qian, Yuntao},
journal = {IET Computer Vision},
title = {Domain-invariant attention network for transfer learning between cross-scene hyperspectral images},
year = {2023},
number = {7},
pages = {739-749},
volume = {17},
doi = {https://doi.org/10.1049/cvi2.12238},
eprint = {https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/cvi2.12238},
keywords = {hyperspectral imaging, pattern classification},
url = {https://ietresearch.onlinelibrary.wiley.com/doi/abs/10.1049/cvi2.12238}
}@article{https://doi.org/10.1049/cvi2.12242,
author = {Zhou, Jun and Xiong, Fengchao and Tong, Lei and Yokoya, Naoto and Ghamisi, Pedram},
journal = {IET Computer Vision},
title = {Guest Editorial: Spectral imaging powered computer vision},
year = {2023},
number = {7},
pages = {723-725},
volume = {17},
doi = {https://doi.org/10.1049/cvi2.12242},
eprint = {https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/cvi2.12242},
url = {https://ietresearch.onlinelibrary.wiley.com/doi/abs/10.1049/cvi2.12242}
}@inproceedings{9883513,
author = {Meng, Zhihao and Ye, Minchao and Yao, Futian and Xiong, Fengchao and Qian, Yuntao},
booktitle = {IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium},
title = {Cross-Scene Hyperspectral Image Classification Based on Cycle-Consistent Adversarial Networks},
year = {2022},
pages = {1912-1915},
doi = {10.1109/IGARSS46834.2022.9883513},
keywords = {Training;Transfer learning;Geoscience and remote sensing;Generative adversarial networks;Generators;Hyperspectral imaging;Image classification;Hyperspectral image classification;heterogeneous transfer learning;cycle-consistent adversarial networks}
}@article{9680683,
author = {Ye, Minchao and Chen, Junbin and Xiong, Fengchao and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Learning a Deep Structural Subspace Across Hyperspectral Scenes With Cross-Domain VAE},
year = {2022},
pages = {1-13},
volume = {60},
doi = {10.1109/TGRS.2022.3142941},
keywords = {Transfer learning;Feature extraction;Training;Sensors;Manifolds;Decoding;Task analysis;Cross-domain variational autoencoder (CDVAE);cross-scene classification;heterogeneous transfer learning;hyperspectral image (HSI)}
}@article{9930129,
author = {Fu, Guanyiman and Xiong, Fengchao and Lu, Jianfeng and Zhou, Jun and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Nonlocal Spatial–Spectral Neural Network for Hyperspectral Image Denoising},
year = {2022},
pages = {1-16},
volume = {60},
doi = {10.1109/TGRS.2022.3217097},
keywords = {Correlation;Noise reduction;Three-dimensional displays;Tensors;Road transportation;Logic gates;Task analysis;Deep learning (DL);global spectral correlation (GSC);hyperspectral image (HSI) denoising;nonlocal self-similarity (NSS);spatial-spectral correlation (SSC)}
}@inproceedings{9746089,
author = {Li, Zhuanfeng and Xiong, Fengchao and Lu, Jianfeng and Zhou, Jun and Qian, Yuntao},
booktitle = {ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title = {Material-Guided Siamese Fusion Network for Hyperspectral Object Tracking},
year = {2022},
pages = {2809-2813},
doi = {10.1109/ICASSP43922.2022.9746089},
keywords = {Training;Target tracking;Image color analysis;Conferences;Signal processing;Feature extraction;Object tracking;Hyperspectral object tracking;feature fusion;material unmixing;appearance modelling}
}@article{9855427,
author = {Xiong, Fengchao and Zhou, Jun and Tao, Shuyin and Lu, Jianfeng and Zhou, Jiantao and Qian, Yuntao},
journal = {IEEE Transactions on Image Processing},
title = {SMDS-Net: Model Guided Spectral-Spatial Network for Hyperspectral Image Denoising},
year = {2022},
pages = {5469-5483},
volume = {31},
doi = {10.1109/TIP.2022.3196826},
keywords = {Noise reduction;Noise measurement;Correlation;Neural networks;Training;Tensors;Sensors;Hyperspectral image denoising;model-based neural network;low-rank representation;multidimensional sparse representation}
}@article{9444347,
author = {Xiong, Fengchao and Zhou, Jun and Tao, Shuyin and Lu, Jianfeng and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {SNMF-Net: Learning a Deep Alternating Neural Network for Hyperspectral Unmixing},
year = {2022},
pages = {1-16},
volume = {60},
doi = {10.1109/TGRS.2021.3081177},
keywords = {Optimization;Training;Sparse matrices;Matrix decomposition;Hyperspectral imaging;Mixture models;Knowledge engineering;Hyperspectral unmixing;model-based neural network;nonnegative matrix factorization (NMF);sparse representation}
}@article{9631264,
author = {Xiong, Fengchao and Zhou, Jun and Zhao, Qinling and Lu, Jianfeng and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {MAC-Net: Model-Aided Nonlocal Neural Network for Hyperspectral Image Denoising},
year = {2022},
pages = {1-14},
volume = {60},
doi = {10.1109/TGRS.2021.3131878},
keywords = {Noise reduction;Mathematical models;Three-dimensional displays;Correlation;Neural networks;Deep learning;Data models;Hyperspectral image (HSI) denoising;low-rank representation;model-based neural network;nonlocal representation}
}@inproceedings{9883667,
author = {Xiong, Fengchao and Ye, Minchao and Zhou, Jun and Qian, Yuntao},
booktitle = {IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium},
title = {Spatial-Spectral Convolutional Sparse Neural Network for Hyperspectral Image Denoising},
year = {2022},
pages = {1225-1228},
doi = {10.1109/IGARSS46834.2022.9883667},
keywords = {Convolutional codes;Visualization;Solid modeling;Three-dimensional displays;Noise reduction;Neural networks;Nonlinear filters;Hyperspectral image denoising;model-based deep learning;convolutional sparse coding;deep un-folding}
}@inproceedings{9884454,
author = {Wang, Chenglong and Ye, Minchao and Lei, Ling and Xiong, Fengchao and Qian, Yuntao},
booktitle = {IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium},
title = {Cross-Domain Attention Network for Hyperspectral Image Classification},
year = {2022},
pages = {1564-1567},
doi = {10.1109/IGARSS46834.2022.9884454},
keywords = {Training;Costs;Transfer learning;Geoscience and remote sensing;Feature extraction;Classification algorithms;Labeling;hyperspectral image;cross-scene classification;few-shot learning;transfer learning;cross-domain attention mechanism}
}@inproceedings{9747001,
author = {Xiong, Fengchao and Ye, Minchao and Zhou, Jun and Lu, Jianfeng and Qian, Yuntao},
booktitle = {ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title = {Multitask Sparse Neural Network for Hyperspectral Image Denoising},
year = {2022},
pages = {2799-2803},
doi = {10.1109/ICASSP43922.2022.9747001},
keywords = {Deep learning;Training;Speech coding;Noise reduction;Neural networks;Signal processing;Task analysis;Hyperspectral image denoising;modelbased neural network;multitask learning;sparse coding}
}@inproceedings{9897277,
author = {Wu, Xiangyu and Lu, Jianfeng and Li, Zhuanfeng and Xiong, Fengchao},
booktitle = {2022 IEEE International Conference on Image Processing (ICIP)},
title = {Ques-to-Visual Guided Visual Question Answering},
year = {2022},
pages = {4193-4197},
doi = {10.1109/ICIP46576.2022.9897277},
keywords = {Location awareness;Visualization;Fuses;Image processing;Semantics;Benchmark testing;Question answering (information retrieval);multi-head attention;multi-modal;visual question answering;channel attention}
}@inbook{doi:https://doi.org/10.1002/9781119687788.ch13,
author = {Qian, Yuntao and Xiong, Fengchao and Ye, Minchao and Zhou, Jun},
chapter = {13},
pages = {363-403},
publisher = {John Wiley & Sons, Ltd},
title = {Model-Inspired Deep Neural Networks for Hyperspectral Unmixing},
year = {2022},
isbn = {9781119687788},
booktitle = {Advances in Hyperspectral Image Processing Techniques},
doi = {https://doi.org/10.1002/9781119687788.ch13},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781119687788.ch13},
keywords = {deep unfolding, hyperspectral unmixing, deep learning, spectral mixture model},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119687788.ch13}
}@inproceedings{9414084,
author = {Xiong, Fengchao and Zhou, Jun and Ye, Minchao and Lu, Jianfeng and Qian, Yuntao},
booktitle = {ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title = {NMF-SAE: An Interpretable Sparse Autoencoder for Hyperspectral Unmixing},
year = {2021},
pages = {1865-1869},
doi = {10.1109/ICASSP39728.2021.9414084},
keywords = {Training;Learning systems;Speech coding;Tools;Decoding;Sparse matrices;Speech processing;Hyperspectral unmixing;model-based neural network;autoencoder;sparse coding}
}@inproceedings{9484032,
author = {Li, Zhuanfeng and Ye, Xinhai and Xiong, Fengchao and Lu, Jianfeng and Zhou, Jun and Qian, Yuntao},
booktitle = {2021 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
title = {Spectral-Spatial-Temporal Attention Network for Hyperspectral Tracking},
year = {2021},
pages = {1-5},
doi = {10.1109/WHISPERS52202.2021.9484032},
keywords = {Training;Deconvolution;Image color analysis;Convolution;Neural networks;Signal processing algorithms;Feature extraction;deep learning;hyperspectral tracking;spectral-spatial-temporal attention}
}@article{9345344,
author = {Wang, Jianxi and Ye, Minchao and Xiong, Fengchao and Qian, Yuntao},
journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title = {Cross-Scene Hyperspectral Feature Selection via Hybrid Whale Optimization Algorithm With Simulated Annealing},
year = {2021},
pages = {2473-2483},
volume = {14},
doi = {10.1109/JSTARS.2021.3056593},
keywords = {Feature extraction;Optimization;Spirals;Space exploration;Search problems;Whales;Training;Cross-domain WOASA;cross-scene feature selection;hyperspectral images}
}@inproceedings{9553257,
author = {Fu, Guanyiman and Xiong, Fengchao and Tao, Shuyin and Lu, Jianfeng and Zhou, Jun and Qian, Yuntao},
booktitle = {2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS},
title = {Learning a Model-Based Deep Hyperspectral Denoiser from a Single Noisy Hyperspectral Image},
year = {2021},
pages = {4131-4134},
doi = {10.1109/IGARSS47720.2021.9553257},
keywords = {Training;Image coding;Noise reduction;Geoscience and remote sensing;Encoding;Numerical models;Noise measurement;Hyperspectral image denoising;model-based deep learning;sparse coding}
}@inproceedings{9647235,
author = {Zou, Shide and Xiong, Fengchao and Luo, Haonan and Lu, Jianfeng and Qian, Yuntao},
booktitle = {2021 Digital Image Computing: Techniques and Applications (DICTA)},
title = {AF-Net: All-scale Feature Fusion Network for Road Extraction from Remote Sensing Images},
year = {2021},
pages = {1-8},
doi = {10.1109/DICTA52665.2021.9647235},
keywords = {Image segmentation;Roads;Digital images;Semantics;Benchmark testing;Feature extraction;Sensors;road extraction;remote sensing images;multiscale feature representation;deep learning;attention}
}@article{Xiong2020,
author = {Xiong, Fengchao and Zhou, Jun and Qian, Yuntao},
journal = {IEEE Transactions on Image Processing},
title = {Material Based Object Tracking in Hyperspectral Videos},
year = {2020},
pages = {3719-3733},
volume = {29},
doi = {10.1109/TIP.2020.2965302},
keywords = {Videos;Hyperspectral imaging;Image color analysis;Object tracking;Feature extraction;Correlation;Object tracking;hyperspectral imaging;material unmixing}
}@inproceedings{9363420,
author = {Ye, Xinhai and Xiong, Fengchao and Lu, Jianfeng and Zhao, Haifeng and Zhou, Jun},
booktitle = {2020 Digital Image Computing: Techniques and Applications (DICTA)},
title = {M2-Net: A Multi-scale Multi-level Feature Enhanced Network for Object Detection in Optical Remote Sensing Images},
year = {2020},
pages = {1-8},
doi = {10.1109/DICTA51227.2020.9363420},
keywords = {Semantics;Object detection;Detectors;Feature extraction;Optical imaging;Task analysis;Remote sensing;Convolutional neural network (CNN);object detection;feature fusion;remote sensing image;multi-scale analysis}
}@article{9210778,
author = {Xiong, Fengchao and Zhou, Jun and Lu, Jianfeng and Qian, Yuntao},
journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title = {Nonconvex Nonseparable Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing},
year = {2020},
pages = {6088-6100},
volume = {13},
doi = {10.1109/JSTARS.2020.3028104},
keywords = {Sparse matrices;Matrix decomposition;Hyperspectral imaging;Linear programming;Estimation;Computational modeling;Generalized minimax concave (GMC) regularization;hyperspectral unmixing;nonnegative matrix factorization (NMF);sparse representation}
}@article{9055228,
author = {Qian, Yuntao and Xiong, Fengchao and Qian, Qipeng and Zhou, Jun},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Spectral Mixture Model Inspired Network Architectures for Hyperspectral Unmixing},
year = {2020},
number = {10},
pages = {7418-7434},
volume = {58},
doi = {10.1109/TGRS.2020.2982490},
keywords = {Artificial neural networks;Estimation;Mixture models;Network architecture;Optimization;Iterative algorithms;Training;Deep unfolding;iterative methods;model-inspired network;spectral unmixing}
}@inproceedings{9191105,
author = {Li, Zhuanfeng and Xiong, Fengchao and Zhou, Jun and Wang, Jing and Lu, Jianfeng and Qian, Yuntao},
booktitle = {2020 IEEE International Conference on Image Processing (ICIP)},
title = {BAE-Net: A Band Attention Aware Ensemble Network for Hyperspectral Object Tracking},
year = {2020},
pages = {2106-2110},
doi = {10.1109/ICIP40778.2020.9191105},
keywords = {Videos;Hyperspectral imaging;Target tracking;Image color analysis;Object tracking;Machine learning;Color;deep learning;hyperspectral tracking;band selection;ensemble learning}
}@inproceedings{9324663,
author = {Xiong, Fengchao and Qian, Kun and Lu, Jianfeng and Zhou, Jun and Qian, Yuntao},
booktitle = {IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium},
title = {Nonlocal Low-Rank Nonnegative Tensor Factorization for Hyperspectral Unmixing},
year = {2020},
pages = {2157-2160},
doi = {10.1109/IGARSS39084.2020.9324663},
keywords = {Tensors;Hyperspectral imaging;Mathematical model;Signal to noise ratio;Matrix decomposition;Sparse matrices;Matrix converters;Hyperspectral unmixing;nonlocal self-similarity;nonnegative tensor factorization;low-rank representation}
}@article{Xiong2019,
author = {Xiong, Fengchao and Qian, Yuntao and Zhou, Jun and Tang, Yuan Yan},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Hyperspectral Unmixing via Total Variation Regularized Nonnegative Tensor Factorization},
year = {2019},
number = {4},
pages = {2341-2357},
volume = {57},
doi = {10.1109/TGRS.2018.2872888},
keywords = {Tensile stress;TV;Hyperspectral imaging;Noise reduction;Algebra;Semantics;Hyperspectral unmixing;nonnegative tensor factorization (NTF);spectral–spatial information;total variation (TV)}
}@inproceedings{8921176,
author = {Xiong, Fengchao and Zhou, Jun and Chanussot, Jocelyn and Qian, Yuntao},
booktitle = {2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
title = {Dynamic Material-Aware Object Tracking in Hyperspectral Videos},
year = {2019},
pages = {1-6},
doi = {10.1109/WHISPERS.2019.8921176},
keywords = {Hyperspectral imaging;Videos;Image color analysis;Object tracking;Feature extraction;Lighting;Hyperspectral unmixing;object tracking;spectral variability;spectral-spatial features}
}@inproceedings{8898675,
author = {Qian, Qipeng and Xiong, Fengchao and Zhou, Jun},
booktitle = {IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium},
title = {Deep Unfolded Iterative Shrinkage-Thresholding Model for Hyperspectral Unmixing},
year = {2019},
pages = {2151-2154},
doi = {10.1109/IGARSS.2019.8898675},
keywords = {Training;Estimation;Iterative methods;Encoding;Optimization;Matching pursuit algorithms;Neural networks;Deep unfolding;spectral unmixing;sparse coding;iterative methods}
}@article{8824180,
author = {Xiong, Fengchao and Zhou, Jun and Qian, Yuntao},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Hyperspectral Restoration via $L_0$ Gradient Regularized Low-Rank Tensor Factorization},
year = {2019},
number = {12},
pages = {10410-10425},
volume = {57},
doi = {10.1109/TGRS.2019.2935150},
keywords = {Noise reduction;Image restoration;Hyperspectral imaging;Matrix decomposition;Correlation;Sparse matrices;Hyperspectral restoration;L₀ gradient regularization;low-rank representation;spectral–spatial information}
}@inproceedings{8451087,
author = {Xiong, Fengchao and Zhou, Jun and Qian, Yuntao},
booktitle = {2018 25th IEEE International Conference on Image Processing (ICIP)},
title = {Hyperspectral Imagery Denoising via Reweighed Sparse Low-Rank Nonnegative Tensor Factorization},
year = {2018},
pages = {3219-3223},
doi = {10.1109/ICIP.2018.8451087},
keywords = {Noise reduction;Tensile stress;Sparse matrices;Image restoration;Hyperspectral imaging;Image coding;Spectral analysis;Hyperspectral imagery;nonnegative tensor factorization;sparse coding;low-rank representation}
}@inproceedings{8518642,
author = {Xiong, Fengchao and Chen, Jingzhou and Zhou, Jun and Qian, Yuntao},
booktitle = {IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium},
title = {Superpixel-Based Nonnegative Tensor Factorization for Hyperspectral Unmixing},
year = {2018},
pages = {6392-6395},
doi = {10.1109/IGARSS.2018.8518642},
keywords = {Tensile stress;Hyperspectral imaging;Roads;Manifolds;Three-dimensional displays;Hyperspectral unmixing;joint spectral-spatial information;superpixel;nonnegative tensor factorization}
}@article{Qian2017,
author = {Qian, Yuntao and Xiong, Fengchao and Zeng, Shan and Zhou, Jun and Tang, Yuan Yan},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
title = {Matrix-Vector Nonnegative Tensor Factorization for Blind Unmixing of Hyperspectral Imagery},
year = {2017},
number = {3},
pages = {1776-1792},
volume = {55},
doi = {10.1109/TGRS.2016.2633279},
keywords = {Tensile stress;Matrix decomposition;Hyperspectral imaging;Mixture models;Feature extraction;Distance measurement;Hyperspectral imagery (HSI);spectral unmixing;spectral-spatial structure;tensor factorization}
}