张永兵
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期刊论文

  • [1] Jingfen Xie, Jian Zhang, Yongbing Zhang, Xiangyang Ji, “PUERT: Probabilistic Under-sampling and Explicable Reconstruction Network for CS-MRI,” accepted by IEEE Journal of Selected Topics in Signal Processing 2022.
  • [2] Jian Zhang, Zhenyu Zhang, Jingfen Xie, Yongbing Zhang, “High-Throughput Deep Unfolding Network for Compressive Sensing MRI,” accepted by IEEE Journal of Selected Topics in Signal Processing 2022.
  • [3] Jun Liao, Xu Chen, Ge Ding, Pei Dong, Hu Ye, Han Wang, Yongbing Zhang, and Jianhua Yao, “Deep learning-based single-shot autofocus method for digital microscopy,” Biomed. Opt. Express, vol. 13, no.1, pp. 314-327, 2022.
  • [4] Bowen Li, Shiyu Tan, Jiuyang Dong, Xiaocong Lian, Yongbing Zhang, Xiangyang Ji, Ashok Veeraraghavan, “3D volumetric microscopy of thick scattering samples using a wide-field microscope and machine learning,” Biomed. Opt. Express, vol. 13, no.1, pp. 284-299, 2022.
  • [5] Yue Huang, Shaowei Jiang, Ruihai Wang, Pengming Song, Jian Zhang, Guoan Zheng, Xiangyang Ji, and Yongbing Zhang, “Ptychography-based high-throughput lensless on-chip microscopy via incremental proximal algorithms,” accepted by Optics Express 2021, vol. 29, no.23, pp.37892-37906.
  • [6] Kaifa Xin, Shaowei Jiang, Xu Chen, Yonghong He, Jian Zhang, Hongpeng Wang, Honghai Liu, Qin Peng, Yongbing Zhang, and Xiangyang Ji, Accelerated Low-cost whole slide imaging system with single-shot autofocusing based on color multiplexed illumination and deep learning, Biomed. Opt. Express, vol. 12, no.9, pp.5644-5657, 2021.
  • [7] Xu Chen, Bowen Li, Shaowei Jiang, Terrance Zhang, Xu Zhang, Peiwu Qin, Xi Yuan, Yongbing Zhang, Guoan Zheng and Xiangyang Ji, Accelerated Phase Shifting for Structured Illumination Microscopy based on Deep Learning, accepted by IEEE Transactions on Computational Imaging 2021, vol. 7, pp. 700-712.
  • [8] Jiangpeng Yan, Shuo Chen, Xiu Li, Yongbing Zhang, “Neural Architecture Search for Compressed Sensing Magnetic Resonance Image Reconstruction,” accepted by Computerized medical imaging and graphics. 2020.
  • [9] Chenggang Yan, Zhisheng Li, Yongbing Zhang, Yutao Liu, Xiangyang Ji, Yongdong Zhang, Depth image denoising using nuclear norm and learning graph model, ACM Transactions on Multimedia Computing, Communications, and Applications (Accept).
  • [10] Yutao Liu, Ke Gu, Xiu Li, Yongbing Zhang, Blind Image Quality Assessment by Natural Scene Statistics and Perceptual Characteristics, ACM Transactions on Multimedia Computing, Communications, and Applications (Accept)
  • [11] Chengfei Guo, Zichao Bian, Shaowei Jiang, Michael Muphy, Jiakai Zhu, Ruihai Wang, Pengming Song, Xiaopeng Shao, Yongbing Zhang, Guoan Zheng, “OpenWSI: a low-cost, high-throughput whole slide imaging system via single-frame autofocusing and open-source hardware,” Optics Letters, vol.45, no.1, pp.260-263, Jan. 2020.
  • [12] Yongbing Zhang, Siyuan Liu, Chao Dong, Xinfeng Zhang, and Yuan Yuan “Multiple Cycle-in-Cycle Generative Adversarial Networks for Unsupervised Image Super-Resolution,” IEEE Trans. on Image Processing (TIP), vo.29,no.4 , pp.1101-1112, 2019
  • [13] Teng Zhang, Shaowei Jiang, Zixin Zhao, Krishna Dixit, Xiaofei Zhou, Jia Hou, Yongbing Zhang, and Chenggang Yan, Rapid and robust two-dimensional phase unwrapping via deep learning, accepted by Optics Express. Optics Express vol.27, no.16, pp.23173-23185, Aug.2019
  • [14] Shaowei Jiang, Zichao Bian, Xizhi Huang, Pengming Song, He Zhang, Yongbing Zhang, and Guoan Zheng, Rapid and robust whole slide imaging based on LED-array illumination and color-multiplexed single-shot dynamic focus tracking, Quantitative Imaging in Medicine and Surgery, vol.9, no.5, pp.823-831, May.2019
  • [15] Pengming Song, Shaowei Jiang, He Zhang, Xizhi Huang, Yongbing Zhang, and Guoan Zheng, Full-field Fourier ptychography (FFP): spatially varying pupil modeling and its application for rapid field-dependent aberration metrology, APL Photonics, vol.4, no.5, pp.050802, 2019
  • [16] Xiu Li, Huaiyu Qi, Shaowei Jiang, Pengming Song, Guoan Zheng, and Yongbing Zhang, Quantitative phase imaging via cGAN network with dual intensity images captured under centrosymmetric illumination, Optics Letters, vol 44, no.11, pp.2879-2882, 2019
  • [17] Chenggang Yan, Yunbin Tu, Xingzheng Wang*, Yongbing Zhang, Xinhong Hao, Yongdong Zhang and Qionghai Dai, “STAT: Spatial-Temporal Attention Mechanism for Video Captioning,” IEEE Trans. Multimedia (TMM)， (高被引)
  • [18] Yutao Liu, Ke Gu, Yongbing Zhang, Xiu Li, Guangtao Zhai, Debin Zhao, and Wen Gao “Unsupervised Blind Image Quality Evaluation via Statistical Measurements of Structure, Naturalness and Perception,” accepted by IEEE Trans. on Circuits and System Video Technology (TCSVT),
  • [19] He Zhang, Shaowei Jiang, Jun Liao, Jian Liu, Yongbing Zhang, and Guoan Zheng, “Near-field Fourier ptychography: super-resolution phase retrieval via speckle illumination,” Optics Express, vol.27, no.5, pp.7498-7512, 2019
  • [20] Yongbing Zhang, Yihui Feng, Xianming Liu, Deming Zhai, Xiangyang Ji, and Qionghai Dai “Color-Guided Depth Image Recovery with Adaptive Data Fidelity and Transferred Graph Laplacian Regularization,” IEEE Trans. on Circuits and System Video Technology (TCSVT), Early Access
  • [21] Yongbing Zhang, Lixin Chen, Chenggang Yan, Peiwu Qin, Xiangyang Ji, and Qionghai Dai “Residual Weighted Convolutional Motion-Compensated Frame Rate Up-Conversion Using Deep Residual Network,” accepted by IEEE Trans. on Circuits and System Video Technology (TCSVT), Early Access.
  • [22] Yongbing Zhang, Tao Shen, Xiangyang Ji, Yun Zhang, Ruiqin Xiong, and Qionghai Dai “Residual Highway Convolutional Neural Networks for in-loop Filtering in HEVC,” IEEE Trans. on Image Processing (TIP), vol. 27, no. 8, pp. 3827-3841, Aug. 2018.
  • [23] Yongbing Zhang, Lulu Sun, Chenggang Yan, Xiangyang Ji, Qionghai Dai “Adaptive Residual Networks for High-Quality Image Restoration,” IEEE Trans. on Image Processing (TIP), vol. 27, no. 7, pp. 3150-3163, Jul. 2018.
  • [24] Tao Dai, Ke Gu, Li Niu, Qingtao Tang, Yongbing Zhang, Weizhi Lu, ShuTao Xia “Referenceless quality metric of multiply-distorted images based on structural degradation,” Neurocomputing , vol. 290, no. 17, May. 2018.
  • [25] Shaowei Jiang, Jun Liao, Zichao Bian, Kaikai Guo, Yongbing Zhang, and Guoan Zheng “Transform and multi-domain deep learning for single-frame rapid autofocusing in whole slide imaging,” Biomedical Optics Express, vol.9, no. 4, 1601-1612, 2018.
  • [26] Yongbing Zhang, Pengming Song, Jian Zhang, and Qionghai Dai, “Fourier ptychographic microscopy with sparse representation,” Scientifics Reports, vol.7, no.1, 2017.
  • [27] Yongbing Zhang, Yulun Zhang, Jian Zhang, Dong Xu, Yun Fu, Xiangyang Ji, and Qionghai Dai, “Collaborative Representation Cascade for Single Image Super-Resolution,” IEEE Transactions on Systems, Man and Cybernetics: Systems 2017, vol.49,no.5,May.2019
  • [28] Yongbing Zhang, Pengming Song, and Qionghai Dai, “Fourier ptychographic microscopy using a Generalized Anscombe Transform approximation of the mixed Poisson-Gaussian likelihood,” Optics Express, vol. 25, no. 1, pp. 168-179, Jan. 2017.
  • [29] Yun Zhang, Xiaoxiang Yang, Xiangkai Liu, Yongbing Zhang, Gangyi Jiang, Sam Kwong “High Efficiency 3D Depth Coding Based on Perceptual Quality of Synthesized Video,” IEEE Trans. on Image Processing (TIP), vol. 25, no. 12, pp. 5877-5891, Dec. 2016.
  • [30] Chen Zhao, Jian Zhang, Siwei Ma, Xiaopeng Fan, Yongbing Zhang, and Wen Gao, “Reducing Image Compression Artifacts by Structural Sparse Representation and Quantization Constraint Prior,” IEEE Trans. on Circuits and System Video Technology (TCSVT), vol. 27, no. 10, pp. 2057-2071, Oct. 2017.
  • [31] Hongwei Qin, Xiu Li, Yangang Wang, Yongbing Zhang, and Qionghai Dai, “Depth Estimation by Parameter Transfer with a Lightweight Model for Single Still Images,” IEEE Trans. on Circuits and System Video Technology (TCSVT), vol. 27, no. 4, pp. 748-759, Apr. 2017.
  • [32] Yongbing Zhang, Huijin Lv, Yebin Liu, Haoqian Wang, Xingzheng Wang, Qian Huang, Xinguang Xiang, and Qionghai Dai, “Light field depth estimation via epipolar plane image analysis and locally linear embedding,” IEEE Trans. on Circuits and System Video Technology (TCSVT), vol. 27, no. 4, pp. 739-747, Apr. 2017.
  • [33] Long Xu, Weisi Lin, Lin Ma, Yongbing Zhang, Yuming Fang, King Ngi Ngan, Songnan Li, and Yihua Yan, “Free-energy Principle Inspired Video Quality Metric and Its Use in Video Coding,” IEEE Trans. Multimedia (TMM), vol. 18, no. 4, pp. 590-602, Apr. 2016.
  • [34] Long Xu, Jia Li, Weisi Lin, Yongbing Zhang, Lin Ma, Yuming Fang, and Yihua Yan, “Multi-task rank learning for image quality assessment,” IEEE Trans. on Circuits and System Video Technology (TCSVT), vol. 27, no. 9, pp. 1833-1843, Sep. 2017.
  • [35] Hangfan Liu, Ruiqin Xiong, Xinfeng Zhang, Yongbing Zhang, Siwei Ma, and Wen Gao, “Non-local gradient sparsity regularization for image restoration,” IEEE Trans. on Circuits and System Video Technology (TCSVT), vol. 27, no. 9, pp. 1909-1921, Sep. 2017.
  • [36] Jian Zhang, Ruiqin Xiong, Chen Zhao, Yongbing Zhang, Siwei Ma, and Wen Gao, “CONCOLOR: Constrained non-convex low-rank model for image deblocking,” IEEE Trans. on Image Processing (TIP), vol. 25, no. 3, pp. 1246-1259, Mar. 2016.
  • [37] Yongbing Zhang, Weixin Jiang, and Qionghai Dai, “Nonlinear optimization approach for Fourier ptychographic microscopy,” Optics Express, vol. 23, no. 26, pp. 33822-33835, Dec. 2015.
  • [38] Yongbing Zhang, Yulun Zhang, Jian Zhang, and Qionghai Dai, “CCR: Clustering and collaborative representation for fast single image super-resolution,” IEEE Trans. Multimedia (TMM), vol. 18, no. 3, pp. 405-417, Mar. 2016.
  • [39] Yongbing Zhang, Long Xu, Xiangyang Ji, and Qionghai Dai, “A Polynomial Approximation Motion Estimation Model for Motion Compensated Frame Interpolation,” IEEE Trans. on Circuits and System Video Technology (TCSVT), vol. 26, no. 8, pp. 1421-1432, Aug. 2016.
  • [40] Yongbing Zhang, Weixin Jiang, Lei Tian, Laura Waller, and Qionghai Dai, “Self-learning based Fourier ptychographic microscopy,” Optics Express, vol. 23, no. 14, pp. 18471-18486, Jul. 2015.
  • [41] Yongbing Zhang, Xiangyang, Haoqian Wang, and Qionghai Dai, “Stereo Interleaving Video Coding with Content Adaptive Image Subsampling,” IEEE Trans. on Circuits and System Video Technology (TCSVT) , vol. 23, no. 7, pp. 1097-1108, Jul. 2013.
  • [42] Yongbing Zhang, Haoqian Wang, and Debin Zhao, “Upsampling oriented frame rate reduction,” Signal Processing: Image Communications vol. 28, pp. 254-266, Mar. 2013. (SCI)
  • [43] Yongbing Zhang, Debin Zhao, Jian Zhang, Ruiqin Xiong and Wen Gao, “Interpolation Dependent Image Downsampling,” IEEE Trans. on Image Processing (TIP), vol 20, no. 11, pp. 3291-3296, Nov. 2011
  • [44] Yongbing Zhang, Xinguang Xiang, Debin Zhao, Siwei Ma and Wen Gao, “Packet video error concealment with auto regressive model,” IEEE Trans. on Circuits and System Video Technology (TCSVT), vol. 22, no. 1, pp. 12-27, Jan. 2012
  • [45] Yongbing Zhang, Debin Zhao, Siwei Ma, Ronggang Wang and Wen Gao, “A Motion Aligned Auto-regressive Model for Frame Rate up Conversion,” IEEE Trans. on Image Processing (TIP), vol 19, no. 5, pp. 1248-1258, May. 2010
  • [46] Yongbing Zhang, Debin Zhao, Xiangyang Ji, Ronggang Wang and Wen Gao, “A Spatio-temporal Auto Regressive Model for Frame Rate up Conversion,” IEEE Trans. on Circuits and System Video Technology (TCSVT), vol. 19, no. 9, pp. 1289-1301, Sep. 2009
  • [47] Yongbing Zhang, Debin Zhao, Hongbin Liu, Yongpeng Li, and Siwei Ma, “Side Information with Auto-regressive Model for Low-delay Distributed Video Coding,” Journal of Visual Communication and Image Representation (JVCIR), vol. 23, no.1, pp. 229-236, Jan. 2012
  • [48] Xiangyang Ji, Yongbing Zhang and Qionghai Dai, “Opposite Parity Packing Arrangement for 3D Stereoscopic Video Coding,” IET Electronics Letters (EL), vol 47, no. 21, pp. 1180-1181, Oct. 2011.

    • 会议论文

    (A list of selected journal publications is available here.)
  • [1] Zhuchen Shao, Yifeng Wang, Yang Chen, Hao Bian, Shaohui Liu, Haoqian Wang, Yongbing Zhang, " LNPL-MIL: Learning from Noisy Pseudo Labels for Promoting Multiple Instance Learning in Whole Slide Image," ICCV 2023
  • [2] Yiyang Lin, Yifeng Wang, Yang Chen, Zirui Zhu, Zijie Fang, Miaorun Lin, and Yongbing Zhang, "Unpaired H&E to PR Stain Transfer with Self-Supervised Auxiliary Segmentation," Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI) 2023
  • [3] Zexin Li, Yiyang Lin, Yifeng Wang, Zijie Fang, Hao Bian, Runze Hu, Xiu Li, and Yongbing Zhang, “ST-MKSC: The FF-FFPE Stain Transfer based on Multiple Key Structure Constraint,” IEEE International Symposium on Biomedical Imaging (ISBI) 2023.
  • [4] Jiale Zhang, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan, “Accurate Image Restoration with Attention Retractable Transformer,” Accepted by ICLR 2023 （入选亮点论文）
  • [5] Zijie Fang, Yang Chen, Yifeng Wang, Zhi Wang, Xiangyang Ji, Yongbing Zhang, “Weakly-Supervised Semantic Segmentation for Histopathology Images Based on Dataset Synthesis and Feature Consistency Constraint,” Accepted by AAAI 2023
  • [6] Zhuchen Shao, Yang Chen, Hao Bian, Jian Zhang, Guojun Liu, Yongbing Zhang, “HVTSurv: Hierarchical Vision Transformer for Patient-level Survival Prediction from Whole Slide Image,” Accepted by AAAI 2023
  • [7] Zheng Chen, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan, “Cross Aggregation Transformer for Image Restoration,” Accepted by NeurIPS 2022 spotlight
  • [8] Bowei Zeng, Yiyang Lin, Yifeng Wang, Yang Chen, Jiuyang Dong, Xi Li, and Yongbing Zhang, “Semi-Supervised PR Virtual Staining for Breast Histopathological Images,” Accepted by MICCAI, Student Travel Award, 2022.
  • [9] Hao Bian, Zhucen Shao, Yang Chen, Yifeng Wang, Haoqian Wang, Jian Zhang, and Yongbing Zhang, “Multiple Instance Learning with Mixed Supervision in Gleason Grading,” Accepted by MICCAI 2022.
  • [10] Yangen Zhan, Hao Bian, Yang Chen, Xiu Li, Yongbing Zhang, “Breast tumor image classification in bright challenge via multiple instance learning and deep transformers,” Accepted by ISBI 2022.
  • [11] Xuanyu Zhang, Yongbing Zhang, Ruiqin Xiong, Qilin Sun, Jian Zhang, “HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive Imaging,” Accepted by CVPR 2022
  • [12] Yiyang Lin, Bowei Zeng, Yang Chen, Yifeng Wang, Zijie Fang, Jian Zhang, Xiangyang Ji, Yongbing Zhang,“Unpaired Multi-Domain Stain Transfer for Kidney Histopathological Images,” Accepted by AAAI 2021.
  • [13] Zhucen Shao, Hao Bian, Yang Chen, Yifeng Wang, Jian Zhang, Xiangyang Ji, Yongbing Zhang,“TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification,” Accepted by NeurIPS 2021.
  • [14] Xiu Li, Jiuyang Dong, Bowen Li, Yi Zhang, Yongbing Zhang, Ashok Veeraraghavan, Xiangyang Ji, “Fast confocal microscopy imaging based on deep learning,” Accepted in ICCP, 2019
  • [15] Lulu Sun, Yongbing Zhang, Chenggang Yan, Xiangyang Ji, Xinhong Hao, Yongdong Zhang, and Qionghai Dai, “Image denoising with local dense and adaptive global residual networks,” Accepted in PCM, 2018 (Best paper award)
  • [16] Tao Dai，Jianrui Cai，Yongbing Zhang，Shu-Tao Xia，Lei Zhang，“Second-order Attention Network for Single Image Super-resolution，” CVPR 2019
  • [17] Yuanyuan, Siyuan Liu, Jiawei Zhang, Yongbing Zhang, Chao Dong, and Liang Lin, “Unsupervised image super-resolution using cycle-in-cycle generative adversarial networks,” accepted by CVPR workshop 2018.
  • [18] Yihui Feng, Xianming Liu, Yongbing Zhang, and Qionghai Dai, “Single depth image super-resolution and denoising based on sparse graphs via structure tensor,” accepted by ICIP 2017.
  • [19] Minghao Yin, Yongbing Zhang, Xiu Li, and Shiqi Wang, “When deep fool meets deep prior: adversarial attack on super-resolution network,” Accepted in ACM Multimedia, Korea, 2018
  • [20] Weixin Jiang, Yongbing Zhang, and Qionghai Dai, “Parameterized reconstruction based Fourier ptychograhy,” Accepted in Proceedings of IEEE International Conference on Multimedia & Expo (ICME), Seattle, USA, Jul, 2016 (oral, top)
  • [21] Yulun Zhang, Yongbing Zhang, Jian Zhang, Haoqian Wang, Xingzheng Wang, and Qionghai Dai, “Adaptive Local Nonparametric Regression for Fast Single Image Super-Resolution,” Accepted in Proceedings of SPIE Visual Communications and Image Processing (VCIP), Singapore, Dec, 2015. (Best student paper award)
  • [22] Xiu Li, Hongwei Qin, Yangang Wang, Yongbing Zhang, Qionghai Dai, DEPT: Depth Estimation by Parameter Transfer for Single Still Images. In ACCV, Nov. 2014, Singapore.
  • [23] Yongbing Zhang, Xingyang Ji, Haoqian Wang, Lei Zhang, and Qionghai Dai, “Content adaptive subsampling for stereo interleaving video coding” in Proceedings of Data Compression Conference (DCC), Snowbird, Utah, USA, pp. 179-188, Apr. 10-12, 2012.
  • [24] Changjun Fu, Xiangyang Ji, Yongbing Zhang, and Qionghai Dai, “A single frame super-resolution method based on matrix completion” in Proceedings of Data Compression Conference (DCC), Snowbird, Utah, USA, pp. 297-306, 2012.
  • [25] Yongbing Zhang, Xinguang Xiang, Siwei Ma, Debin Zhao, and Wen Gao, “Auto regressive model and weighted least squares based packet video error concealment” in Proceedings of Data Compression Conference (DCC), Snowbird, Utah, USA, pp. 455-464, Mar.24-26, 2010.
  • [26] Yongbing Zhang, Haoqian Wang, and Debin Zhao, “Upsampling dependent frame rate reduction for low bit rate video coding,” in Proceedings of Data Compression Conference (DCC), Snowbird, Utah, USA, pp. 489, Mar.29-31, 2011.