Journals and Conference Papers (since 2010)

Google Scholar Link for Yao Wang

2024

  1. Haoyang Pei, Timothy M. Shepherd, Yao Wang, Fang Liu, Daniel K. Sodickson, Noam Ben-Eliezer, Li Feng. “DeepEMC-T2 mapping: Deep learning–enabled T2 mapping based on echo modulation curve modeling.” in Magnetic Resonance in Medicine.

  2. Janjusevic, N., Khalilian-Gourtani, A., Flinker, A., Feng, L., & Wang, Y. (2024). “GroupCDL: Interpretable Denoising and Compressed Sensing MRI via Learned Group-Sparsity and Circulant Attention“. arXiv preprint arXiv:2407.18967, 2024.

  3. Zhongzheng Yuan, Samyak Rawlekar, Siddharth Garg, Elza Erkip, Yao Wang. “Split Computing With Scalable Feature Compression for Visual Analytics on the Edge“. In IEEE Transactions on Multimedia, 2024.

  4. Chen, Junbo, Vara Lakshmi Bayanagari, Sohae Chung, Yao Wang, and Yvonne W. Lui. “Deep learning with diffusion MRI as in vivo microscope reveals sex-related differences in human white matter microstructure.” In Scientific Reports, 2024.

  5. Chen, X., Wang, R., Khalilian-Gourtani, A., Yu, L., Dugan, P., Friedman, D., Doyle, W., Devinsky, O., Wang, Y. and Flinker. “A Neural Speech Decoding Framework Leveraging Deep Learning and Speech Synthesis“. In Nature Machine Intelligence, April, 2024 (press link)

  6. Yueyu Hu, Ran Gong, Qi Sun, and Yao Wang, “Low Latency Point Cloud Rendering with Learned Splatting“. in Proc. of IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) Workshop (AIS: Vision, Graphics and AI for Streaming), 2024. (Code)

  7. Yueyu Hu, Ran Gong, and Yao Wang, “Bits-to-Photon: End-to-End Learned Scalable Point Cloud Compression for Direct Rendering“. in arXiv:2406.05915, 2024.
  8. Fan, Zhipeng, and Yao Wang. “Lightweight Estimation of Hand Mesh and Biomechanically Feasible Kinematic Parameters.” arXiv preprint arXiv:2303.14838 (2023).

2023

  1. Z. Yuan, S. Garg, E. Erkip, Y. Wang. “Scalable Feature Compression for Edge-Assisted Object Detection Over Time-Varying Networks“. In MLSys 2023 Workshop on Resource-Constrained Learning in Wireless Networks.
     
  2. J. Chen, S. Chung, T. Li, E. Fieremans, D. S. Novikov, Y. Wang and Y.W. Lui. “Identifying relevant diffusion MRI microstructure biomarkers relating to exposure to repeated head impacts in contact sport athletes“. The Neuroradiology Journal. 2023;0(0). doi:10.1177/19714009231177396.
     
  3. O. Aristizábal, Z. Qiu, E. Gallego, M. Aristizábal, J. Mamou, Y. Wang, … & D. H. Turnbull (2023). “Longitudinal in Utero Analysis of Engrailed-1 Knockout Mouse Embryonic Phenotypes Using High-Frequency Ultrasound“. Ultrasound in Medicine & Biology, 49(1), 356-367.
     
  4. S. Mehrdad., F.E. Shamout, Y. Wang, & S. F. Atashzar (2023). ”Deep learning for deterioration prediction of COVID‐19 patients based on time‐series of three vital signs”. Sci Rep 13, 9968 (2023). https://doi.org/10.1038/s41598-023-37013-3
     
  5. Z. Chen, E. Shemuelian, G. Wollstein, Y. Wang, H. Ishikawa and J.S. Schuman, 2023. “Segmentation-Free OCT-Volume-Based Deep Learning Model Improves Point-Wise Visual Field Threshold Estimation“. Investigative Ophthalmology & Visual Science, 12(6).
     
  6. Y. Wang and D. Mukherjee, “The Discrete Cosine Transform and Its Impact on Visual Compression: Fifty Years From Its Invention [Perspectives],” in IEEE Signal Processing Magazine, vol. 40, no. 6, pp. 14-17, Sept. 2023, doi: 10.1109/MSP.2023.3282775.
     
  7. Hao, Y., Feng, J., Rizzo, J. R., Wang, Y., & Fang, Y. (2023). Detect and Approach: Close-Range Navigation Support for People with Blindness and Low Vision. In European Conference on Computer Vision, pp. 607-622. Cham: Springer Nature Switzerland, 2022
     
  8. Hao, Y., Pei, H., Lyu, Y., Yuan, Z., Rizzo, J. R., Wang, Y., & Fang, Y. (2023). Understanding the Impact of Image Quality and Distance of Objects to Object Detection Performance. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023 (pp. 11436–11442). Institute of Electrical and Electronics Engineers Inc.
     
  9. Mao, Y., Liu, H., Wang, Y., & Brenner, E. D. (2023). A deep learning approach to track Arabidopsisseedlings’ circumnutation from time-lapse videos. Plant Methods, 19.
     
  10. Pei, H., Xia, D., Xu, X., Yang, Y., Wang, Y., Liu, F., & Feng, L. (2023). Rapid 3D T mapping using deep learning-assisted Look-Locker inversion recovery MRI. Magnetic Resonance in Medicine, 90, 569–582.
     
  11. Wang, Ran, Xupeng Chen, Amirhossein Khalilian-Gourtani, Leyao Yu, Patricia Dugan, Daniel Friedman, Werner Doyle, Orrin Devinsky, Yao Wang, and Adeen Flinker. “Distributed feedforward and feedback cortical processing supports human speech production.” in Proceedings of the National Academy of Sciences 120, no. 42 (2023): e2300255120.

2022

  1. Z. Yuan, S. Rawlekar, S. Garg, E. Erkip and Y. Wang, “Feature Compression for Rate Constrained Object Detection on the Edge,” 2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR), 2022, pp. 1-6, doi: 10.1109/MIPR54900.2022.00008.
     
  2. Y. Mao, Y. Hu and Y. Wang, “Learning to Predict on Octree for Scalable Point Cloud Geometry Coding,” 2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR), 2022, pp. 96-102, doi: 10.1109/MIPR54900.2022.00024.
     
  3. N. Janjušević, A. Khalilian-Gourtani and Y. Wang, “Gabor is Enough: Interpretable Deep Denoising with a Gabor Synthesis Dictionary Prior,” 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), 2022, pp. 1-5, doi: 10.1109/IVMSP54334.2022.9816313.
     
  4. Z. Yuan, T. Azzino, Y. Hao, Y. Lyu, H. Pei, A. Boldini, M. Mezzavilla, M. Beheshti, M. Porfiri, T.E. Hudson, W. Seiple, Yi, Fang, S. Rangan, Y. Wang, J.R. Rizzo, “Network-Aware 5G Edge Computing for Object Detection: Augmenting Wearables to “See” More, Farther and Faster,” in IEEE Access, vol. 10, pp. 29612-29632, 2022, doi: 10.1109/ACCESS.2022.3157876.
     
  5. N. Janjušević, A. Khalilian-Gourtani and Y. Wang, “CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and Demosaicing,” in IEEE Open Journal of Signal Processing, doi: 10.1109/OJSP.2022.3172842.
     
  6. S. Chung, J. Chen, T. Li, Y. Wang and Y.W. Lui, “Investigating Brain White Matter in Football Players with and without Concussion Using a Biophysical Model from Multishell Diffusion MRI.” in American Journal of Neuroradiology, doi: https://doi.org/10.3174/ajnr.A7522.
     
  7. L. Sun, Y. Mao, T. Zong, Y. Liu and Y. Wang, “Live 360 Degree Video Delivery based on User Collaboration in a Streaming Flock,” in IEEE Transactions on Multimedia, doi: 10.1109/TMM.2022.3149642.
     
  8. H. Liu, M. Lu, Z. Chen, X. Cao, Z. Ma and Y. Wang, “End-to-End Neural Video Coding Using a Compound Spatiotemporal Representation,” in IEEE Transactions on Circuits and Systems for Video Technology, vol. 32, no. 8, pp. 5650-5662, Aug. 2022, doi: 10.1109/TCSVT.2022.3150014.
     
  9. Y. Hu and Y. Wang, “Learning Neural Volumetric Field for Point Cloud Geometry Compression,” 2022 Picture Coding Symposium (PCS), San Jose, CA, USA, 2022, pp. 127-131, doi: 10.1109/PCS56426.2022.10018029.
     
  10. Fitzgerald Jones, K., Fu, M.R., McTernan, M.L., Ko, E., Yazicioglu, S., Axelrod, D., Guth, A.A., Miaskowski, C., Conley, Y.P., Wood, L.J. and Wang, Y., 2022. “Lymphatic Pain in breast cancer survivors “. Lymphatic Research and Biology, 20(5), pp.525-532.
     
  11. Fu, M.R., McTernan, M.L., Qiu, J.M., Miaskowski, C., Conley, Y.P., Ko, E., Axelrod, D., Guth, A., Somers, T.J., Wood, L.J. and Wang, Y., 2022. “Co-occurring Fatigue and Lymphatic Pain Incrementally Aggravate Their Negative Effects on Activities of Daily Living, Emotional Distress, and Overall Health of Breast Cancer Patients“. Integrative Cancer Therapies, 21, p.15347354221089605.
     
  12. Fu, M. R., Axelrod, D., Guth, A. A., Scagliola, J., Rampertaap, K., El-Shammaa, N., … & Wang, Y. (2022). “A web-and mobile-based intervention for women treated for breast cancer to manage chronic pain and symptoms related to lymphedema: Results of a randomized clinical trial“. JMIR cancer, 8(1), e29485.
     
  13. Z. Chen, E. Shemuelian, L. Zheng, G. Wollstein, Y. Wang, H. Ishikawa and J.S. Schuman, 2022. “Segmentation-Free OCT-Volume-Based Deep Learning Model Improves Point-Wise Visual Field Threshold Estimation“. Investigative Ophthalmology & Visual Science, 63(7), pp.852-852.
     
  14. Yixiang Mao, Liyang Sun, Yong Liu, Yao Wang, 2024. “Interactive 360° Video Streaming Using FoV-Adaptive Coding with Temporal Prediction“. arXiv preprint arXiv:2403.11155.

2021

  1. H. Liu, M. Lu, Z. Ma, F. Wang, Z. Xie, X. Cao and Y. Wang, “Neural Video Coding Using Multiscale Motion Compensation and Spatiotemporal Context Model,” in IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 8, pp. 3182-3196, Aug. 2021, doi: 10.1109/TCSVT.2020.3035680.
     
  2. T. Chen, H. Liu, Z. Ma, Q. Shen, X. Cao and Y. Wang, “End-to-End Learnt Image Compression via Non-Local Attention Optimization and Improved Context Modeling,” in IEEE Transactions on Image Processing, vol. 30, pp. 3179-3191, 2021, doi: 10.1109/TIP.2021.3058615. 
     
  3. Z. Chen, R. Wang, H. Liu and Y. Wang, “PDWN: Pyramid Deformable Warping Network for Video Interpolation,” in IEEE Open Journal of Signal Processing, doi: 10.1109/OJSP.2021.3075879  
     
  4.  Z. Qiu, T. Xu, J. Langerman, W. Das, C. Wang, N. Nair, O. Aristizábal, J. Mamou, D.H. Turnbull, J.A. Ketterling and Y. Wang, “A Deep Learning Approach for Segmentation, Classification, and Visualization of 3-D High-Frequency Ultrasound Images of Mouse Embryos”, in IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 68, pp. 2460-2471, Mar. 2021, doi: 10.1109/TUFFC.2021.3068156.
     
  5. Z. Yuan, H. Liu, D. Mukherjee, B. Adsumilli and Y. Wang, “Block-based Learned Image Coding with Convolutional Autoencoder and Intra-Prediction Aided Entropy Coding,” 2021 Picture Coding Symposium (PCS), 2021, pp. 1-5, doi: 10.1109/PCS50896.2021.9477503.
     
  6. L. Sun, T. Zong, S. Wang, Y. Liu and Y. Wang, “Towards Optimal Low-Latency Live Video Streaming,” in IEEE/ACM Transactions on Networking, vol. 29, no. 5, pp. 2327-2338, Oct. 2021, doi: 10.1109/TNET.2021.3087625
     
  7. Z. Fan, J. Liu and Y. Wang, “Motion Adaptive Pose Estimation from Compressed Videos,” 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 11699-11708, doi: 10.1109/ICCV48922.2021.01151.
     
  8. C. Sohae, J. Chen, T. Li, Y. Wang, YW. Lui, “White Matter Microstructural Alterations In Contact-Sport Athletes With And Without Concussion: A Multi-Shell Diffusion Study,” International Society for Magnetic Resonance in Medicine (ISMRM), 2021.
     
  9. L. Sun, T. Zong, S. Wang, Y. Liu and Y. Wang, “Tightrope walking in low-latency live streaming: optimal joint adaptation of video rate and playback speed,” in Proceedings of the 12th ACM Multimedia Systems Conference, 2021.

2020

  1. A. Khalilian-Gourtani, S. Minaee and Y. Wang, “Masked-RPCA: Moving Object Detection With an Overlaying Model,” in IEEE Open Journal of Signal Processing, vol. 1, pp. 274-286, 2020  
     
  2. Jeffrey Mao*, Junbo Chen*, Cassandra Thiel, Yao Wang, “iWaste Video-Based Medical Waste Detection and Classification,” in IEEE Engineering in Medicine and Biology Confrence(EMBC), * equal contribution.  
     
  3. Tongda Xu*, Ziming Qiu*, William Das, Chuiyu Wang, Jack Langerman, Nitin Nair, Orlando Aristizabal, Jonathan Mamou, Daniel H. Turnbull, Jeffrey A. Ketterling, Yao Wang, “Deep Mouse: An End-to-end Auto-context Refinement Framework for Brain Ventricle & Body Segmentation in Embryonic Mice Ultrasound Volumes,” in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020), * equal contribution.   
     
  4. Wang Ran, Xupeng Chen, Amirhossein Khalilian-Gourtani, Zhaoxi Chen, Leyao Yu, Adeen Flinker, Yao Wang, “Stimulus Speech Decoding From Human Cortex with Generative Adversarial Network Transfer Learning” in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020), (best paper award finalist) 
     
  5. Yixiang Mao, Liyang Sun, Yong Liu, and Yao Wang. 2020. Low-latency FoV-adaptive Coding and Streaming for Interactive 360° Video Streaming. In Proceedings of the 28th ACM International Conference on Multimedia (MM 2020). 
     
  6. Liyang Sun, Yixiang Mao, Tongyu Zong, Yong Liu, and Yao Wang. 2020. Flocking-based live streaming of 360-degree video. In Proceedings of the 11th ACM Multimedia Systems Conference (MMSys 2020). 
     
  7. Zhipeng Fan, Jun Liu, Yao Wang: Adaptive computationally efficient network for monocular 3d hand pose estimation. In Proceedings of the European Conference on Computer Vision (ECCV 2020). 
     
  8. Zhiqi Chen, Yao Wang, Gadi Wollstein, Maria de los Angeles Ramos-Cadena, Joel S. Schuman, HiroshiIshikawa (2020). ”Macular GCIPL Thickness Map Prediction via Time-Aware Convolutional LSTM.” In 2020 IEEE International Symposium on Biomedical Imaging (ISBI).
     
  9. Liu, Haojie, Ming Lu, Zhan Ma, Fan Wang, Zhihuang Xie, Xun Cao, and Yao Wang. “Neural Video Coding using Multiscale Motion Compensation and Spatiotemporal Context Model.” IEEE Transactions on Circuits and Systems for Video Technology (2020). 
     
  10. Junbo Chen, Sohae Chung, Joseph Rath, Els Fieremans, YaoWang, Yvonne Lui, “Predicting Visual-Motor Functioning in Patients with Mild Traumatic Brain Injury from Multi-Shell Diffusion MRI using Gradient Boosting Tree,” Annual Meeting of Radiological Society of North America (RSNA), 2020.
     
  11. Z. Chen, Y. Wang, M. de los Angeles Ramos-Cadena, G. Wollstein, JS. Schuman, H. Ishikawa, “Predicting Macular Progression Map Using Deep Learning,” Investigative Ophthalmology & Visual Science. 2020 Jun 10;61(7):4532-.

2019

  1. Xu, Tongda, Xiyan Cai, Yao Wang, Xiuyuan Wang, Sohae Chung, Els Fieremans, Joseph Rath, Steven Flanagan, and Yvonne W. Lui. “Identification of relevant diffusion MRI metrics impacting cognitive functions using a novel feature selection method.” in IEEE IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 2019.  
     
  2. Ziming Qiu, Nitin Nair, Jack Langerman, Orlando Aristizable, Jonathan Mamou, Daniel H. Turnbull, Jeffrey A. Ketterling, Yao Wang, “Automatic Mouse Embryo Brain Ventricle & Body Segmentation and Mutant Classification from Ultrasound Data Using Deep Learning,” in IEEE International Ultrasonics Symposium (IUS), 2019. 
     
  3. Chuanmin Jia,  Zhaoyi Liu,  Yao Wang,  Siwei Ma, Wen Gao, “Layered Image Compression using Scalable Auto-encoder”, IEEE 2nd International Conference on Multimedia Information Processing and Retrieval (MIPR’2019),  Mar. 2019, Best Student Paper Award.
                       
  4. Minaee, S., Wang, Y., Aygar, A., Chung, S., Wang, X., Lui, Y. W., … & Rath, J, “MTBI Identification From Diffusion MR Images Using Bag of Adversarial Visual Features.” in Transactions on Medical Imaging (TMI), 2019.
                       
  5. L. Sun, F. Duanmu, Y. Liu, Y. Wang, Y. Ye, H. Shi, and D. Dai, “A Two-Tier System for On-Demand Streaming of 360 Degree Video Streaming over Dynamic Networks,” in IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), 2019.
                       
  6. S. Minaee and Y. Wang, “An ADMM Approach to Masked Signal Decomposition Using Subspace Representation,” in IEEE Transactions on Image Processing. doi: 10.1109/TIP.2019.2894966.
                       
  7. Chenge Li, Weixi Zhang, Yong Liu, Yao Wang, “Very Long Term Field of View Prediction for 360-degree Video Streaming“, invited paper in IEEE Multimedia Information Processing and Retrieval (MIPR), 2019.

2018

  1. Qian Huang, Weixin Zhu, Yang Zhao, Linsen Chen, Yao Wang, Tao Yue, Xun Chao, “Multispectral Image Intrinsic Decomposition via Subspace Constraint,” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT,  June 2018, pp. 6430-6439.
    doi: 10.1109/CVPR.2018.00673
                       
  2. Fu, Mei R., Yao Wang, Chenge Li, Zeyuan Qiu, Deborah Axelrod, Amber A. Guth, Joan Scagliola et al. “Machine learning for detection of lymphedema among breast cancer survivors.” mHealth 4, no. 5 (2018).
                       
  3. A. Chiang, Q. Chen, Y. Wang and M. R. Fu, “Kinect-Based In-Home Exercise System for Lymphatic Health and Lymphedema Intervention,” in IEEE Journal of Translational Engineering in Health and Medicine, vol. 6, pp. 1-13, 2018, Art no. 4100313.
                       
  4. Ziming Qiu, Jack Langerman, Nitin Nair, Orlando Aristizabal, Jonathan Mamou, Daniel H. Turnbull, Jeffrey Ketterling, Yao Wang, “Deep BV: A Fully Automated System for Brain Ventricle Localization and Segmentation in 3D Ultrasound Images of Embryonic Mice“, IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 2018, accepted, arXiv preview link.                                                                                                                                                                                                                    
  5. Shervin Minaee, Yao Wang, Anna Choromanska, Sohae Chung, Xiuyuan Wang, Els Fieremans, Steven Flanagan, Joseph Rath, Yvonne W Lui, “A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRI”, International Engineering in Medicine and Biology Conference (EMBC), IEEE, 2018.
     
  6. Shervin Minaee, Yao Wang, Alp Aygar, Sohae Chung, Xiuyuan Wang, Yvonne W. Lui, Els Fieremans, Steven Flanagan, Joseph Rath “MTBI Identification From Diffusion MR Images Using Bag of Adversarial Visual Features”, IEEE Transactions on Medical Imaging (Under Review).
     
  7. R. Wang, Y. Song, Y. Wang and J. Viventi, “Long-term prediction of μECOG signals with a spatio-temporal pyramid of adversarial convolutional networks,” 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), Washington, DC, 2018, pp. 1313-1317. doi: 10.1109/ISBI.2018.8363813
     
  8. Jen-wei Kuo, Ziming Qiu, Orlando Aristizbal, Jonathan Mamou, Daniel H. Turnbull, Jeffrey Ketterling, and Yao Wang, Automatic Body Localization and Brain Ventricle Segmentation in 3D High Frequency Ultrasound Images of Mouse Embryos, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), Washington, DC, 2018, pp. 635-639.
     
  9. Yuwen He, Xiaoyu Xiu, Phillipe Hanhart, Yan Ye, Fanyi Duanmu, and Yao Wang, “Content-Adaptive 360-degree Video Coding Using Hybrid Cubemap Projection,” IEEE Picture Coding Symposium (PCS), San Francisco, California, USA, 2018.
     
  10. Fanyi Duanmu, Zhan Ma, Meng Xu, and Yao Wang, “An HEVC-Compliant Fast Screen Content Transcoding Framework Based on Mode Mapping,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2018. 
     
  11. Liyang Sun, Fanyi Duanmu, Yong Liu, Yao Wang, Yihua Ye, Hang Shi, David Dai, Multi-path Multi-tier 360-degree Video Streaming in 5G Networks, ACM Multimedia System Conference (MMSys), Amsterdam, Netherland, 2018.
     
  12. Fanyi Duanmu, Yixiang Mao, Shuai Liu, Sumanth Srinivasan, and Yao Wang, “A Subjective Study of Viewer Navigation Behaviors When Watching 360-degree Videos on Computers,” in Proc. of IEEE International Conference on Multimedia Expo (ICME), San Diego, California, USA, 2018. 
     
  13. Fanyi Duanmu, Yuwen He, Xiaoyu Xiu, Phillipe Hanhart, Yan Ye, and Yao Wang, Hybrid Cubemap Projection Format for 360-degree Video Coding, IEEE Data Compression Conference (DCC), Snowbird, Utah, 2018.
     
  14. Fanyi Duanmu, Xin Feng, Xiaoqing Zhu, Dan Tan, and Yao Wang, A Multi-View Pedestrian Tracking Framework Based on Graph Matching, IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR), Miami, Florida, USA, 2018.
     
  15. Yuan Wang, Yao Wang, Yvonne W Lui, Dynamic Causal Modelling with neuron firing model in generalized recurrent neural network framework, ISMRM 2018. Preview
     
  16. An-Ti Chiang, Qi Chen, Yao Wang and Mei R. Fu. Motion Sequence Alignment for a Kinect-Based In-Home Exercise System for Lymphatic Health and Lymphedema Intervention, International Engineering in Medicine and Biology Conference (EMBC), IEEE, 2018.
     
  17. Yuan Wang, Yao Wang, Yvonne W. Lui, Generalized Recurrent Neural Network accommodating Dynamic Causal Modeling for functional MRI analysis, NeuroImage, Volume 178, 2018, Pages 385-402, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2018.05.042 (http://www.sciencedirect.com/science/article/pii/S105381191830449X)
     
  18. Yuan Wang, Yao Wang, Yvonne W. Lui, BIOPHYSICALLY INTERPRETABLE RECURRENT NEURAL NETWORK AND SPARSITY BASED CAUSAL ARCHITECTURE DISCOVERY, International Engineering in Medicine and Biology Conference (EMBC), IEEE, 2018.
                       
  19. A. Khalilian-Gourtani, Y. Wang and J. Mamou, “Scanning Acoustic Microscopy Image Super-Resolution using Bilateral Weighted Total Variation Regularization,” 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, USA, 2018, pp. 5113-5116.
                       
  20. Wang, R., Wang, Y., Flinker, A., (2018, December). “Reconstructing Speech Stimuli From Human Auditory Cortex Activity Using a WaveNet-like Network”. In Signal Processing in Medicine and Biology Symposium (SPMB), 2018 IEEE. https://arxiv.org/abs/1811.02694

2017

 
  1. E. Kurdoglu, Y. Liu, Y. Wang, Perceptual Quality Maximization for Video Calls with Packet Losses by Optimizing FEC, Frame Rate and Quantization, IEEE Transactions on Multimedia, 2017.
     
  2. Yuanyi Xue, Yao Wang, A Novel Video Coding Framework using Self-adaptive Dictionary, IEEE Transactions on Circuits and Systems for Video Technology, Oct. 2017.
     
  3. Fanyi Duanmu, Zhan Ma, Meng Xu and Yao Wang, HEVC-Compliant Screen Content Transcoding Based on Mode Mapping and Fast Termination, IEEE Visual Communications and Image Processing (VCIP), 2017.
     
  4. S Minaee, Y Wang, “Text Extraction From Texture Images Using Masked Signal Decomposition”, Global Conference on Signal and Information Pro-cessing, IEEE, 2017.
     
  5. S Minaee, Wang Y, Chung S, Wang X, Fieremans E, Flanagan S, Rath J, Lui YW., “A Machine Learning Approach For Identifying Patients with Mild Traumatic Brain Injury Using Diffusion MRI Modeling”, ASFNR 12th Annual Meeting, 2017 (Accepted).
     
  6. Jen-wei Kuo, Jonathan Mamou, Yao Wang, Emi Saegusa-Beecroft, Junji Machi, and Ernest J. Feleppa, Segmentation of 3D High-frequency Ultrasound Images of Human Lymph Nodes Using Graph Cut with Energy Functional Adapted to Local Intensity Distribution, Transactions on Ultrasonics Ferroelectrics and Frequency Control (TUFFC), 2017.
     
  7. Yilin Song, Yao Wang and Jonathan Viventi, Unsupervised Learning of Spike Pattern for Seizure Detection and Wavefront Estimation of High Resolution Micro Electrocorticographic (μECoG) Data, IEEE transactions on nanobioscience 16.6 (2017): 418-427.
     
  8. An-Ti Chiang, Qi Chen, Shijie Li, Yao Wang and Mei R. Fu. Denoising of Joint Tracking Data by Kinect Sensors Using Clustered Gaussian Process Regression Proceedings of the 2nd International Workshop on Multimedia for Personal Health and Health Care. ACM, 2017.
     
  9. Fanyi Duanmu, Eymen Kurdoglu, S. Amir Hosseini, Yong Liu and Yao Wang, Prioritized Buffer Control in Two-tier 360 Video Streaming, ACM SigComm Workshop on VR/AR Network, 2017.
     
  10. Fanyi Duanmu, Eymen Kurdoglu, Yong Liu, Yao Wang, View Direction and Bandwidth Adaptive 360 Degree Video Streaming Using a Two-Tier System, IEEE International Symposium on Circuits and Systems (ISCAS), 2017.
     
  11. Shervin Minaee, Yao Wang, Subspace Learning in The Presence of Sparse Structured Outliers and Noise, IEEE International Symposium on Circuits and Systems, 2017.
     
  12. Shervin Minaee, Yao Wang, Palmprint Recognition Using Deep Scattering Convolutional Network, IEEE International Symposium on Circuits and Systems, 2017.
     
  13. Yuan Wang, Yao Wang, Yvonne W Lui, Generalized Recurrent Neural Network accommodating Dynamic Causal Modelling for functional MRI analysis, ISMRM, 2017.

2016

  1. Chenge Li, An-Ti Chiang, Gregory Dobler, Yao Wang, Kun Xie, Kaan Ozbay, Masoud Ghandehari, J. Zhou, and D. Wang, “Robust vehicle tracking for urban traffic videos at intersections“, In Advanced Video and Signal Based Surveillance (AVSS), 2016 13th IEEE International Conference on, pp. 207-213, IEEE, 2016.
     
  2. Kun Xie, Chenge Li, Kaan Ozbay, Gregory Dobler, Hong Yang, An-Ti Chiang, and Masoud Ghandehari. “Development of a comprehensive framework for video-based safety assessment“, In Intelligent Transportation Systems (ITSC), 2016 IEEE 19th International Conference on, pp. 2638-2643. IEEE, 2016.
     
  3. Shervin Minaee and Yao Wang, “Image Segmentation Using Overlapping Group Sparsity“, Signal Processing in Medicine and Biology Symposium, IEEE, 2016.
     
  4. Shervin Minaee and Yao Wang, Screen Content Image Segmentation Using Robust Regression and Sparse Decomposition, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2016.
     
  5. Fanyi Duanmu; Zhan Ma; Yao Wang, Fast Mode and Partition Decision Using Machine Learning for Intra-Frame Coding in HEVC Screen Content Coding Extension, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2016.
     
  6. Shervin Minaee and Yao Wang, “Screen Content Image Segmentation Using Sparse Decomposition and Total Variation Minimization”, IEEE International Conference on Image Processing, 2016.
     
  7. Fanyi Duanmu; Zhan Ma; Wei Wang; Meng Xu; Yao Wang, A novel screen content fast transcoding framework based on statistical study and machine learning, IEEE International Conference on Image Processing, 2016.
     
  8. Eymen Kurdoglu, Yong Liu and Yao Wang, “Real-time Bandwidth Prediction and Rate Estimation for Video Calls over Cellular Networks”, ACM Multimedia Systems Conference, 2016.
     
  9. Eymen Kurdoglu, Yong Liu and Yao Wang, “Dealing With User Heterogeneity in P2P Multi-Party Video Conferencing: Layered Distribution Versus Partitioned Simulcast”, IEEE Transactions on Multimedia, vol. 18, no. 1, 2016.

2015

 
  1. Shervin Minaee, AmirAli Abdolrashidi and Yao Wang, Screen Content Image Segmentation Using Sparse-Smooth Decomposition”, Asilomar Conference on Signals,Systems, and Computers, IEEE, 2015.
     
  2. Shervin Minaee and Yao Wang, “Fingerprint Recognition Using Translation Invariant Scattering Network”, IEEE Signal Processing in Medicine and Biology Symposium (SPMB), Philadelphia, Pennsylvania, 2015.
     
  3. Yilin Song, Jonathan Viventi and Yao Wang, “Seizure Prediction Through Clustering and Temporal Analysis of Micro Electrocorticographic Data”, The IEEE Signal Processing in Medicine and Biology Symposium (SPMB), Philadelphia, Pennsylvania, 2015 [poster]
     
  4. Shervin Minaee, AmirAli Abdolrashidi and Yao Wang, “Iris Recognition Using Scattering Transform and Textural Features”, Signal Processing Workshop, IEEE, 2015.
     
  5. Shervin Minaee and Yao Wang, “Screen Content Image Segmentation using Least Absolute Deviation Fitting”, IEEE International Conference on Image Processing (ICIP), Québec, Canada, 2015.
     
  6. Fanyi Duanmu, Zhan Ma, Yao Wang, Fast CU Partition Decision Using Machine Learning for Screen Content Compression, IEEE International Conference on Image Processing (ICIP), Québec, Canada, 2015.
     
  7. Zhili Guo, Yao Wang, Xiaoqing Zhu, “Assessing the Visual Effect of Non-periodic Temporal Variation of Quantization Stepwise in Compressed Video”, IEEE International Conference on Image Processing (ICIP), Québec, Canada, 2015.
     
  8. Xinchen Ye, Jingyu Yang, Xin Sun, Kun Li, Chunping Hou, Yao Wang, “Foreground-Background Separation From Video Clips via Motion-assisted Matrix Restoration”, IEEE Transactions on Circuits and Systems for Video Technology, 2015.
     
  9. Zhili Guo, Yao Wang, Elza Erkip, Shivendra Panwar, “Wireless Video Multicast With Cooperative and Incremental Transmission of Parity Packets“, IEEE Transactions on Multimedia, 2015.
     
  10. Jen-wei Kuo, Yao Wang, O. Aristizabal, D. H. Turnbull, J. Ketterling, J. Mamou, “Automatic mouse embryo brain ventricle segmentation, gestation stage estimation, and mutant detection from 3D 40-MHz ultrasound data,” in Ultrasonics Symposium (IUS), 2015 [poster]
     
  11. Jen-wei Kuo, Jonathan Mamou, Yao Wang, Emi Saegusa-Beecroft, Junji Machi, Ernest J. Feleppa, “A Novel Nested Graph Cuts Method for Segmenting Human Lymph Nodes in 3D High Frequency Ultrasound Images”, International Symposium on Biomedical Imaging: From Nano to Macro, 2015.
     
  12. Jen-wei Kuo, Jonathan Mamou, Orlando Aristizbal, Xuan Zhao, Jeffrey A. Ketterling, and Yao Wang, Nested Graph Cut for Automatic Segmentation of High-Frequency Ultrasound Images of the Mouse Embryo, IEEE Transactions on Medical Imaging (TMI), vol. 35, no. 2, pp. 427-441, Sep. 2015.

2014

 
  1. Xinchen Ye, Jingyu Yang, Hao Huang, Chunping Hou, Yao Wang, “Computational multi-view imaging with Kinect”, IEEE Transactions on Broadcasting, vol. 60, no. 3, pp. 540-554, Sept. 2014.
     
  2. Jingyu Yang, Xinchen Ye, Kun Li, Chunping Hou, Yao Wang, “Color-guided depth recovery from RGB-D data using an adaptive autoregressive model”, IEEE Transactions on Image Processing, vol. 23, no. 8, pp. 3443-3458, 2014
     
  3. Yuanyi Xie, Yao Wang, “Video coding using a self-adaptive redundant dictionary consisting of spatial and temporal prediction candidates”, IEEE International Conference on Multimedia and Expo (ICME), July, 2014.
     
  4. An-Ti Chiang, Yao Wang, “Human detection in fish-eye images using hog-based detectors over rotated windows”, IEEE International Conference on Multimedia and Expo (ICME), July, 2014.
     
  5. Eymen Kurdoglu, Yong Liu, and Yao Wang, “Dealing with User Heterogeneity in P2P Multiparty Video Conferencing: Layered Coding Versus Receiver Partitioning“, in Proc. of Communication and Networking Techniques for Contemporary Video Workshop (in conjunction with INFOCOM), 2014 / Toronto, Canada
     
  6. Yen-Fu Ou, Yuanyi Xue, Yao Wang, “Q-STAR: A Perceptual Video Quality Model Considering Impact of Spatial, Temporal, and Amplitude Resolutions”, IEEE Transactions on Image Processing, Vol. 23, no. 6, pp. 2473- 2486, June, 2014.
  7. Yvonne W. Lui, Yuanyi Xue, Damon Kenul, Yulin Ge, Robert I. Grossman, and Yao Wang. “Classification algorithms using multiple MRI features in mild traumatic brain injury.” Neurology, vol. 83, no. 14, pp. 1235-1240. 2014.

2013

 
  1. Shervin Minaee, Yao Wang and Yvonne W Lui, “Prediction of Longterm Outcome of Neuropsychological Tests of MTBI Patients Using Imaging Features,” Accepted, IEEE Signal Processing in Medicine and Biology Symposium, December 2013.
     
  2. Hao Hu, Xiaoqing Zhu, Yao Wang, Rong Pan, Jiang Zhu and Flavio Bonomi, “Proxy-Based Multi-Stream Scalable Video Adaptation over Wireless Networks Using Subjective Quality and Rate Models,” IEEE trans. on Multimedia, vol. 15, no. 7, pp. 1638-1652, Nov. 2013.
     
  3. Xinggong Zhang, Yang Xu, Hao Hu, Yong Liu, Zongming Guo and Yao Wang, “Modeling and Analysis of Skype Video Calls: Rate Control and Video Quality,” IEEE trans. on Multimedia, vol. 15, no. 6, pp. 1446-1457, Oct. 2013.
     
  4. Jen-wei Kuo, Yao Wang, Orlando Aristizabal, Jeffrey A. Ketterling, Jonathan Mamou, “Automatic Mouse Embryo Brain Ventricle Segmentation from 3D 40-MHz Ultrasound Data,” IEEE International Ultrasonics Symposium (IUS), July 2013.
     
  5. Zhan Ma, Felix CA Fernandes, and Yao Wang, “Analytical rate model for compressed video considering impacts of spatial, temporal and amplitude resolutions,“IEEE International Conference on Multimedia and Expo Workshops (ICMEW), July, 2013.
     
  6. Meng Xu, and Yao Wang, “One-pass mode decision for low-complexity and high-efficiency encoding of quality scalable video,” IEEE International Conference on Multimedia and Expo Workshops (ICMEW), July, 2013.
     
  7. Zhili Guo, Yao Wang, Elza Erkip, and Shivendra Panwar, “Video multicast through cooperative incremental parity packet transmission,” In Proceedings of the 5th Workshop on Mobile Video (MoVid ’13), Oslo, Norway, February 2013.

2012

 
  1. Yue Deng, Yebin Liu, Qionghai Dai, Zengke Zhang, Yao Wang, “Noisy Depth Maps Fusion for Multiview Stereo Via Matrix Completion,” IEEE Journal . Sel. Topics Signal Processing 6(5): 566-582, Sept, 2012.
     
  2. Hao Hu, Zhan Ma and Yao Wang, “Optimization of spatial, temporal and amplitude resolution for rate-constrained video coding and scalable video adaptation,” IEEE ICIP, Sept. 2012.
     
  3. Hao Hu, Xiaoqing Zhu, Yao Wang, Rong Pan, Jiang Zhu and Flavio Bonomi, “QoE-based Multi-Stream Scalable Video Adaptation over Wireless Networks with Proxy,” accepted to IEEE ICC workshop on Realizing Advanced Video Optimized Wireless Networks, June, 2012
     
  4. Xuan Zhao, Dewen Kong, Jenghwa Chang, Edward K. Wong, Gabor Jozsef, Silvia C. Formenti, Yao Wang, “Automatic beam placement for breast radiotherapy using a Support Vector Machine based algorithm,” Med. Phys. 39, 2536-2543, May, 2012.
     
  5. Z. Ma, M. Xu, Y. Ou and Y. Wang, “Modeling Rate and Perceptual Quality of Video as Functions of Quantization and Frame Rate and Its Applications,” IEEE Trans. Circuits and Systems for Video Technology, vol. 22, no. 5, pp. 671-682, May 2012.
     
  6. Xinggong Zhang, Yang Xu, Hao Hu, Yong Liu, Zongming Guo and Yao Wang, “Profiling Skype Video Calls: Rate Control and Video Quality,” accepted to IEEE INFOCOM, March, 2012
     
  7. Zhan Ma, Felix C. A. Fernandes, and Yao Wang, “Power-Rate-Quality Optimized Scalable Video Adaptation,” Proc. of IEEE CISS, Princeton NJ, March. 2012

2011

 
  1. Z. Ma, H. Hu and Y. Wang, “On Complexity Modeling of H.264 Video Decoding and Its Application for Energy Efficient Decoding,” IEEE Trans. on Multimedia, vol. 13, no. 6, pp. 1240-1255, December 2011.
     
  2. O. Alay, P. Liu, Y. Wang, E. Erkip and S. S. Panwar, “Cooperative Layered Video Multicast using Randomized Distributed Space Time Codes,” IEEE Trans. Multimedia, vol.13, no.5, pp.1127-1140, Oct. 2011.
     
  3. Zhan Ma, Meng Xu and Yao Wang, Modeling Video Rate as a Function of Frame Size, Frame Rate and Quantization Stepsize, Proc. of IEEE Multimedia Signal ProcessingWorkshop (MMSP2011), Hangzhou, China, Oct. 2011 (withdrawn).
     
  4. Zhan Ma, Meng Xu, Kyeong Yang and Yao Wang, Modeling Rate and Perceptual Quality of Video and Its Application to Frame Rate Adaptive Rate Control, Proc. of IEEE Int. Conf. Image Processing (ICIP2011), Brussels, Belgium, Sept. 2011.
     
  5. Hao Hu, Yang Guo and Yong Liu, “Peer-to-Peer Streaming of Layered Video: Efficiency, Fairness and Incentive,” IEEE trans. on CSVT, Vol. 21, No. 8, pp. 1013-1026, Aug. 2011.
     
  6. Y.-F. Ou, Y. Xue, Z. Ma and Y. Wang, ”A Perceptual Video Quality Model for Mobile Platform Considering Impact of Spatial, Temporal, and Amplitude Resolutions,” 2011 IEEE IVMSP (Image, Video, and Multidimensional Signal Processing Technical Committee) Workshop on Perception and Visual Signal Analysis, pp.117-122, Ithaca, NY, June 2011.
     
  7. Xun Cao, Alan Bovik, Yao Wang and Qionghai Dai, “Converting 2D video to 3D: An Efficient Path to a 3D Experience,” in IEEE Multimedia, Volume 18, Issue 4, pp.12-17, April, 2011.
     
  8. Z. Ma and Y. Wang, “Power consumption model for scalable video decoding on mobile platform,” IEEE Com-Soc Multimedia Communications Technical Committee E-Letter, Vol. 6, no.5, May 2011, pp 20-23. Invited contribution.
     
  9. X. Feng, T. Liu, D. Yang D, and Y. Wang, “Saliency inspired full-reference quality metrics for packet-lossimpaired video,” IEEE Trans. Broadcasting, March 2011, vol. 57, pp. 81-88.
     
  10. Y.-F. Ou, Z. Ma, T. Liu, and Y. Wang. ”Perceptual quality assessment of video considering both frame rate and quantization artifacts,” IEEE Trans. Circuits & Systems for Video Technology, Mar. 2011. vol. 21, pp. 286-298.

2010

 
  1. Y. Xue, Y.-F. Ou, Z. Ma and Y. Wang, ”Perceptual video quality assessment on a mobile platform considering both spatial resolution and quantization artifacts,” Special session on Perceptual Quality Assessment In Networked Video Applications, Proc. 18th Intl. Packet Video Workshop (PV2010), Dec. 2010, Hong Kong.
     
  2. X. Zhao, E. Wong, Y. Wang, S. Lymberis, B. Wen, S. Formenti, J. H. Chang, “A support vector machine for predicting preferred treatment position in radiotherapy of patients with breast cancer,” Medical Physics, vol. 57, pp. 5341-5350, Oct. 2010.
     
  3. O. Alay, Y. Wang, E. Erkip, S. Panwar, “Wireless Video Multicast using R-DSTC,” IEEE ComSoc E-Letter of Multimedia Communications Technical Committee, Volume 5, No 5, September, 2010, pp 44-47.
     
  4. O. Alay, T. Korakis, Y. Wang, E. Erkip, S. Panwar, “Layered Wireless Video Multicast Using Relays,” IEEE Transactions on Circuits and Systems for Video Technology, Volume 20, No 8, Aug. 2010, pp 1095-1109
     
  5. Z. Ma, H. Hu and Y. Wang, “DVFS-enabled Energy Ecient Video Decoding,” IEEE ComSoc MMTC E-letter, vol. 5, no. 4, July 2010, pp. 20-24. Invited contribution.
     
  6. O. Alay, Z. Guo, Y. Wang, E. Erkip, S. Panwar, “Enhanced Parity Packet Transmission for Video Multicast using R-DSTC,” IEEE PIMRC, July 2010.
     
  7. O. Alay, T. Korakis, Y. Wang, S. Panwar, “Dynamic Rate and FEC Adaptation for Video Multicast in Multi-rate Wireless Networks,” to appear, ACM/Springer Mobile Networks and Applications (MONET), Special Issue on Advances In Wireless Testbeds and Research Infrastructures, June, 2010 .
     
  8. Z. Liu, Z. Wu, P. Liu, H. Liu, and Y. Wang,”Layer Bargaining: Multicast Layered Video over Wireless Networks,” IEEE Journal on Selected Areas in Communications (JSAC). Special Issue on Wireless Video, April 2010, pp. 445-455.
     
  9. O. Alay, T. Korakis, Y. Wang, S. Panwar, “Dynamic Rate and FEC Adaptation for Video Multicast in Multi-rate Wireless Networks,” ACM/Springer Mobile Networks and Applications (MONET), Special Issue on Advances In Wireless Testbeds and Research Infrastructures, Volume 15, Number 3, April, 2010, pp 425-434.
     
  10. C. Bilen, I. Selesnick, Y. Wang, R. Otazo, D. Kim, L. Axel, and D. Sodickson, “On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regulation,” In Proc. of IEEE ICIP, Mar. 2010.
     
  11. Y.-F. Ou, Z. Ma, and Y. Wang. ”Perceptual quality of video with frame rate variation: a subjective study,” In Proc. of IEEE ICIP, Mar. 2010.
     
  12. O. Alay, P. Liu, Y. Wang, E. Erkip, S. Panwar, “Error Resilient Video Multicast using Randomized Distributed Space-time Codes,” in IEEE ICASSP, Dallas, TX, March, 2010.
     
  13. Zhengye Liu, Hao Hu, Yong Liu, Keith. W. Ross, Yao Wang, and Markus Mobius, “P2P Trading Incentives in Online Social Networks: The Value of Staying Connected,” IEEE Conference on Computer Communications (INFOCOM’10), March, 2010.