Sharon Xiaolei Huang

Professor

Sharon Xiaolei Huang

Publication Tags

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Neural Networks Polymers Convolutional Neural Networks Nanocomposites Experiments Learning Image Resolution Hot Temperature Machine Learning Datasets Image Retrieval Network Architecture Health Poly(Vinylidene Fluoride Co Hexafluoro Propylene) Object Detection Screening Color Image Quality Pixels Semantics Image Segmentation Neoplasms Learning Systems Therapeutics Traffic Signs

Most Recent Publications

Zebrafish Histotomography Noise Removal in Projection and Reconstruction Domains

Amogh Subbakrishna Adishesha, Daniel Vanselow, Patrick La Riviere, Sharon Xiaolei Huang, Keith Cheng, on p. 140-144

Sinogram domain angular upsampling of sparse-view micro-CT with dense residual hierarchical transformer and attention-weighted loss

Amogh Subbakrishna Adishesha, Daniel J. Vanselow, Patrick La Riviere, Keith C. Cheng, Sharon X. Huang, 2023, Computer Methods and Programs in Biomedicine

AI Chatbots in Clinical Laboratory Medicine: Foundations and Trends

He S. Yang, Fei Wang, Matthew B. Greenblatt, Sharon X. Huang, Yi Zhang, 2023, Clinical Chemistry on p. 1238-1246

ABSLearn: a GNN-based framework for aliasing and buffer-size information retrieval

Ke Liang, Jim Tan, Dongrui Zeng, Yongzhe Huang, Xiaolei Huang, Gang Tan, 2023, Pattern Analysis and Applications on p. 1171-1189

BBox-Guided Segmentor: Leveraging expert knowledge for accurate stroke lesion segmentation using weakly supervised bounding box prior

Yanglan Ou, Sharon X. Huang, Kelvin K. Wong, Jonathon Cummock, John Volpi, James Z. Wang, Stephen T.C. Wong, 2023, Computerized Medical Imaging and Graphics

Forecasting User Interests Through Topic Tag Predictions in Online Health Communities

Amogh Subbakrishna Adishesha, Lily Jakielaszek, Fariha Azhar, Peixuan Zhang, Vasant Honavar, Fenglong Ma, Chandra Belani, Prasenjit Mitra, Sharon Xiaolei Huang, 2023, IEEE Journal of Biomedical and Health Informatics on p. 3645-3656

Editorial for special issue on explainable and generalizable deep learning methods for medical image computing

Guotai Wang, Shaoting Zhang, Xiaolei Huang, Tom Vercauteren, Dimitris Metaxas, 2023, Medical Image Analysis

Cross-identity Video Motion Retargeting with Joint Transformation and Synthesis

Haomiao Ni, Yihao Liu, Sharon X. Huang, Yuan Xue, 2023, on p. 412-422

Cross-identity Video Motion Retargeting with Joint Transformation and Synthesis

Haomiao Ni, Yihao Liu, Sharon Huang, Yuan Xue, 2023, on p. 412--422

Semi-supervised body parsing and pose estimation for enhancing infant general movement assessment

Haomiao Ni, Yuan Xue, Liya Ma, Qian Zhang, Xiaoye Li, Sharon X. Huang, 2023, Medical Image Analysis

Most-Cited Papers

Global contrast based salient region detection

Ming Ming Cheng, Niloy J. Mitra, Xiaolei Huang, Philip H.S. Torr, Shi Min Hu, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence on p. 569-582

StackGAN: Text to Photo-Realistic Image Synthesis with Stacked Generative Adversarial Networks

Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, Dimitris Metaxas, 2017, on p. 5908-5916

AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, Xiaodong He, 2018, on p. 1316-1324

Traffic-Sign Detection and Classification in the Wild

Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu, 2016, on p. 2110-2118

StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, Dimitris N. Metaxas, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence on p. 1947-1962

SegAN: Adversarial Network with Multi-scale L <sub>1</sub> Loss for Medical Image Segmentation

Yuan Xue, Tao Xu, Han Zhang, L. Rodney Long, Xiaolei Huang, 2018, Neuroinformatics on p. 383-392

SPDA-CNN: Unifying semantic part detection and abstraction for fine-grained recognition

Han Zhang, Tao Xu, Mohamed Elhoseiny, Xiaolei Huang, Shaoting Zhang, Ahmed Elgammal, Dimitris Metaxas, 2016, on p. 1143-1152

SalientShape: Group saliency in image collections

Ming Ming Cheng, Niloy J. Mitra, Xiaolei Huang, Shi Min Hu, 2014, Visual Computer on p. 443-453

Phase-field modeling and machine learning of electric-thermal-mechanical breakdown of polymer-based dielectrics

Zhong Hui Shen, Jian Jun Wang, Jian Yong Jiang, Sharon X. Huang, Yuan Hua Lin, Ce Wen Nan, Long Qing Chen, Yang Shen, 2019, Nature Communications

Multimodal deep learning for cervical dysplasia diagnosis

Tao Xu, Han Zhang, Xiaolei Huang, Shaoting Zhang, Dimitris N. Metaxas, 2016, on p. 115-123

News Articles Featuring Sharon Xiaolei Huang

Mar 07, 2023

College of IST awards seed grants to 8 projects

The Penn State College of Information Sciences and Technology recently announced eight projects that will receive funding from the college’s seed grant program.

Full Article

Oct 26, 2022

Researchers to use $1.2 million grant to study early Alzheimer’s detection

A team of Penn State-led researchers received a $1.2 million grant from the National Institutes of Health to help fund a project to develop a machine learning system for early Alzheimer’s disease detection. Alzheimer’s disease, a neurological condition and the most common form of dementia, affects nearly 6 million Americans, according to the Centers for Disease Control and Prevention.

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Oct 07, 2020

Podcast unpacks interdisciplinary team’s rapid new virus diagnostics

The latest episode of The Symbiotic Podcast welcomes its largest-ever crew of guests, collaborators from a multi-disciplinary, multi-institution team that came together via video conference to talk about their work on a newly developed rapid diagnostic tool for COVID-19 and other viruses.

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Feb 07, 2020

Penn State receives five-year $3.7 million grant to study virus evolution

The evolution of viruses will be the focus of a five-year $3.7 million dollar grant from the National Science Foundation’s new program on convergence research, to an interdisciplinary team led by Penn State. The grant is in two phases, depending on successful completion of phase one milestones.

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