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2020 – today
- 2024
[j15]Xi Tan, Xuan Liu
, Kai Xiang, Jing Wang, Shan Tan:
Deep Filtered Back Projection for CT Reconstruction. IEEE Access 12: 20962-20972 (2024)- [j14]Susu Kang, Yixiong Kang, Shan Tan:
Exploring and Exploiting Multi-Modality Uncertainty for Tumor Segmentation on PET/CT. IEEE J. Biomed. Health Informatics 28(9): 5435-5446 (2024) - [c26]Jun Cheng, Dong Liang, Shan Tan:
Transfer CLIP for Generalizable Image Denoising. CVPR 2024: 25974-25984 - [c25]Dong Liang, Yuji Du, Shan Tan:
Siamese Contrastive Reverse Distillation for Industrial Anomaly Localization. FAIML 2024: 200-203 - [c24]Yuji Du, Xuanyan Wu, Hao Yang, Dong Liang, Jianing Jin, Dongning Su, Chengzhang He, Yun Ling, Zhonglue Chen, Kang Ren, Tao Feng, Shan Tan:
Deep Learning Models for Discrimination of Parkinson's disease and Multiple System Atrophy on Brain Magnetic Resonance Imaging. FAIML 2024: 310-313 - [i6]Jun Cheng, Dong Liang, Shan Tan:
Transfer CLIP for Generalizable Image Denoising. CoRR abs/2403.15132 (2024) - 2023
- [j13]Susu Kang, Zhiyuan Chen, Laquan Li, Wei Lu, X. Sharon Qi, Shan Tan:
Learning feature fusion via an interpretation method for tumor segmentation on PET/CT. Appl. Soft Comput. 148: 110825 (2023) - [j12]Susu Kang, Muyuan Yang, X. Sharon Qi, Jun Jiang, Shan Tan:
Bridging Feature Gaps to Improve Multi-Organ Segmentation on Abdominal Magnetic Resonance Image. IEEE J. Biomed. Health Informatics 27(3): 1477-1487 (2023) - [c23]Tao Liu, Jun Cheng, Shan Tan:
Spectral Bayesian Uncertainty for Image Super-Resolution. CVPR 2023: 18166-18175 - [c22]Xin Cai, Shan Tan:
BSDIB: Balanced Self-Distillation Information Bottleneck for Long-Tailed Visual Recognition. FAIML 2023: 37-40 - [c21]Jun Cheng, Tao Liu, Shan Tan:
Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising. ICCV 2023: 12891-12902 - [i5]Xuan Liu, Yaoqin Xie, Songhui Diao, Shan Tan, Xiaokun Liang:
A Diffusion Probabilistic Prior for Low-Dose CT Image Denoising. CoRR abs/2305.15887 (2023) - [i4]Jun Cheng, Tao Liu, Shan Tan:
Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising. CoRR abs/2308.04682 (2023) - [i3]Xuan Liu, Yaoqin Xie, Songhui Diao, Shan Tan, Xiaokun Liang:
Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains. CoRR abs/2308.16742 (2023) - [i2]Jingwei Niu, Jun Cheng, Shan Tan:
Image Denoising via Style Disentanglement. CoRR abs/2309.14755 (2023) - 2022
- [j11]Haosen Liu, Laquan Li, Jiangbo Lu, Shan Tan:
Group Sparsity Mixture Model and Its Application on Image Denoising. IEEE Trans. Image Process. 31: 5677-5690 (2022) - [c20]Tao Liu, Shan Tan:
Decoupled Frequency Learning for Dynamic Scene Deblurring. ICPR 2022: 89-96 - [c19]Yunfei Han, Shan Tan:
TwinLSTM: Two-channel LSTM Network for Online Action Detection. ICPR 2022: 3310-3317 - 2021
- [j10]Fucui Xu, Shan Tan:
Deep learning with multiple scale attention and direction regularization for asset price prediction. Expert Syst. Appl. 186: 115796 (2021) - [c18]Haosen Liu, Xuan Liu, Jiangbo Lu, Shan Tan:
Self-Supervised Image Prior Learning with GMM from a Single Noisy Image. ICCV 2021: 2825-2834 - 2020
- [j9]Laquan Li, Xiangming Zhao, Wei Lu, Shan Tan:
Deep learning for variational multimodality tumor segmentation in PET/CT. Neurocomputing 392: 277-295 (2020) - [c17]Fucui Xu, Shan Tan:
Dynamic Portfolio Management Based on Pair Trading and Deep Reinforcement Learning. CIIS 2020: 50-55
2010 – 2019
- 2019
- [j8]Haosen Liu, Shan Tan:
Image Regularizations Based on the Sparsity of Corner Points. IEEE Trans. Image Process. 28(1): 72-87 (2019) - 2018
- [j7]Mathieu Hatt, Baptiste Laurent, Anouar Ouahabi, Hadi Fayad, Shan Tan, Laquan Li, Wei Lu, Vincent Jaouen, Clovis Tauber, Jakub Czakon, Filip Drapejkowski, Witold Dyrka, Sorina Camarasu-Pop, Frédéric Cervenansky, Pascal Girard, Tristan Glatard, Michaël Kain, Yao Yao, Christian Barillot, Assen Kirov, Dimitris Visvikis:
The first MICCAI challenge on PET tumor segmentation. Medical Image Anal. 44: 177-195 (2018) - [j6]Binbin Chen, Kai Xiang, Zaiwen Gong, Jing Wang, Shan Tan:
Statistical Iterative CBCT Reconstruction Based on Neural Network. IEEE Trans. Medical Imaging 37(6): 1511-1521 (2018) - [c16]Sadegh Riyahi, Wookjin Choi, Chia-Ju Liu, Saad Nadeem, Shan Tan, Hualiang Zhong, Wengen Chen, Abraham J. Wu, James G. Mechalakos, Joseph O. Deasy, Wei Lu:
Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response. DATRA/PIPPI@MICCAI 2018: 31-41 - [i1]Sadegh Riyahi, Wookjin Choi, Chia-Ju Liu, Saad Nadeem, Shan Tan, Hualiang Zhong, Wengen Chen, Abraham J. Wu, James G. Mechalakos, Joseph O. Deasy, Wei Lu:
Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response. CoRR abs/1808.08312 (2018) - 2017
- [j5]Laquan Li, Jian Wang, Wei Lu, Shan Tan:
Simultaneous tumor segmentation, image restoration, and blur kernel estimation in PET using multiple regularizations. Comput. Vis. Image Underst. 155: 173-194 (2017) - [j4]Liang Liu, Xinxin Li, Kai Xiang, Jing Wang, Shan Tan:
Low-Dose CBCT Reconstruction Using Hessian Schatten Penalties. IEEE Trans. Medical Imaging 36(12): 2588-2599 (2017) - [c15]Hua Yang, Jipu Gao, Changbao Xu, Zheng Long, Weigang Feng, Shaohua Xiong, Shuaiwei Liu, Shan Tan:
Infrared image change detection of substation equipment in power system using random forest. ICNC-FSKD 2017: 1745-1751
2000 – 2009
- 2009
- [c14]Tan Shan, Ioannis A. Kakadiaris:
Kernel active contour. ICCV 2009: 521-528 - 2008
- [j3]Tan Shan, Licheng Jiao, Ioannis A. Kakadiaris:
Wavelet-Based Bayesian Image Estimation: From Marginal and Bivariate Prior Models to Multivariate Prior Models. IEEE Trans. Image Process. 17(4): 469-481 (2008) - [j2]Alberto Santamaría-Pang, Teodor Stefan Bildea, Tan Shan, Ioannis A. Kakadiaris:
Denoising for 3-D Photon-Limited Imaging Data Using Nonseparable Filterbanks. IEEE Trans. Image Process. 17(12): 2312-2323 (2008) - 2007
- [j1]Tan Shan, Licheng Jiao:
Multivariate Statistical Models for Image Denoising in the Wavelet Domain. Int. J. Comput. Vis. 75(2): 209-230 (2007) - 2005
- [c13]Tan Shan, Licheng Jiao:
new evidences for sparse coding strategy employed in visual neurons: from the image processing and nonlinear approximation viewpoint. ESANN 2005: 441-446 - [c12]Xiangrong Zhang, Shuang Wang, Tan Shan, Licheng Jiao:
Radar target recognition using SVMs with a wrapper feature selection driven by immune clonal algorithm. ESANN 2005: 577-582 - [c11]Tan Shan, Shuang Wang, Xiangrong Zhang, Licheng Jiao:
Automatic Image Enhancement Driven by Evolution Based on Ridgelet Frame in the Presence of Noise. EvoWorkshops 2005: 304-313 - [c10]Xiangrong Zhang, Shuang Wang, Tan Shan, Licheng Jiao:
Selective SVMs Ensemble Driven by Immune Clonal Algorithm. EvoWorkshops 2005: 325-333 - [c9]Tan Shan, Xiangrong Zhang, Licheng Jiao:
Dual ridgelet frame constructed using biorthogonal wavelet basis. ICASSP (2) 2005: 997-1000 - [c8]Xiangrong Zhang, Tan Shan, Shuang Wang, Licheng Jiao:
SAR Image Segmentation Using Kernel Based Spatial FCM. ICIAR 2005: 48-54 - [c7]Tan Shan, Licheng Jiao:
Monoscale Dual Ridgelet Frame. ICIAR 2005: 263-269 - [c6]Tan Shan, Xiuli Ma, Xiangrong Zhang, Licheng Jiao:
A Review: Relationship Between Response Properties of Visual Neurons and Advances in Nonlinear Approximation Theory. ISNN (1) 2005: 51-56 - [c5]Tan Shan, Xiangrong Zhang, Shuang Wang, Licheng Jiao:
Image Representation in Visual Cortex and High Nonlinear Approximation. ISNN (1) 2005: 57-62 - [c4]Wentao Huang, Licheng Jiao, Tan Shan, Maoguo Gong:
Response Analysis of Neuronal Population with Synaptic Depression. NIPS 2005: 523-530 - 2004
- [c3]Tan Shan, Xiangrong Zhang, Licheng Jiao:
A Brushlet-Based Feature Set Applied to Texture Classification. CIS 2004: 1175-1180 - [c2]Tan Shan, Licheng Jiao, Xiangchu Feng:
Ridgelets Frame. ICIAR (1) 2004: 479-476 - [c1]Xiangrong Zhang, Tan Shan, Licheng Jiao:
SAR Image Classification Based on Immune Clonal Feature Selection. ICIAR (2) 2004: 504-511
Coauthor Index
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