Tzu-Ming Harry Hsu
Tzu-Ming Harry Hsu
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα - Αρχική σελίδα
Παρατίθεται από
Παρατίθεται από
Measuring the effects of non-identical data distribution for federated visual classification
TMH Hsu, H Qi, M Brown
arXiv preprint arXiv:1909.06335, 2019
Clinically Accurate Chest X-Ray Report Generation
G Liu, TMH Hsu, M McDermott, W Boag, WH Weng, P Szolovits, ...
Machine Learning for Healthcare Conference, 249-269, 2019
3d-aware scene manipulation via inverse graphics
S Yao, TMH Hsu, JY Zhu, J Wu, A Torralba, WT Freeman, JB Tenenbaum
arXiv preprint arXiv:1808.09351, 2018
Unsupervised domain adaptation with imbalanced cross-domain data
T Ming Harry Hsu, W Yu Chen, CA Hou, YH Hubert Tsai, YR Yeh, ...
Proceedings of the IEEE International Conference on Computer Vision, 4121-4129, 2015
Transfer Neural Trees for Heterogeneous Domain Adaptation
WY Chen, TMH Hsu, YHH Tsai, YCF Wang, MS Chen
Computer Vision (ECCV), 2016 European Conference on, 2016
Learning food quality and safety from wireless stickers
U Ha, Y Ma, Z Zhong, TM Hsu, F Adib
Proceedings of the 17th ACM Workshop on Hot Topics in Networks, 106-112, 2018
Federated visual classification with real-world data distribution
TMH Hsu, H Qi, M Brown
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Baselines for chest x-ray report generation
W Boag, TMH Hsu, M McDermott, G Berner, E Alesentzer, P Szolovits
Machine Learning for Health Workshop, 126-140, 2020
Unsupervised Multimodal Representation Learning across Medical Images and Reports
TMH Hsu, WH Weng, W Boag, M McDermott, P Szolovits
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018, 2018
Chexpert++: Approximating the chexpert labeler for speed, differentiability, and probabilistic output
MBA McDermott, TMH Hsu, WH Weng, M Ghassemi, P Szolovits
Machine Learning for Healthcare Conference, 913-927, 2020
Transfer neural trees: Semi-supervised heterogeneous domain adaptation and beyond
WY Chen, TMH Hsu, YHH Tsai, MS Chen, YCF Wang
IEEE Transactions on Image Processing 28 (9), 4620-4633, 2019
Three-dimensional neural network to automatically assess liver tumor burden change on consecutive liver MRIs
A Goehler, TMH Hsu, R Lacson, I Gujrathi, R Hashemi, G Chlebus, ...
Journal of the American College of Radiology 17 (11), 1475-1484, 2020
Adversarial Contrastive Pre-training for Protein Sequences
M McDermott, B Yap, H Hsu, D Jin, P Szolovits
arXiv preprint arXiv:2102.00466, 2021
Automatic Longitudinal Assessment of Tumor Responses
Massachusetts Institute of Technology, 2020
Connecting the dots without clues: Unsupervised domain adaptation for cross-domain visual classification
WY Chen, TMH Hsu, CA Hou, YR Yeh, YCF Wang
2015 IEEE International Conference on Image Processing (ICIP), 3997-4001, 2015
Artificial intelligence to assess body composition on routine abdominal CT scans and predict mortality in pancreatic cancer–a recipe for your local application
TMH Hsu, K Schawkat, SJ Berkowitz, JL Wei, A Makoyeva, K Legare, ...
European Journal of Radiology 142, 109834, 2021
Visceral adiposity and severe COVID-19 disease: application of an artificial intelligence algorithm to improve clinical risk prediction
A Goehler, HTM Tsu, JA Seiglie, MJ Siedner, J Lo, V Triant, J Hsu, ...
Open Forum Infectious Diseases, 2021
Methods and apparatus for radio frequency sensing in diverse environments
U Ha, J Leng, A Khaddaj, Y Ma, TM Hsu, Z Zhong, F Adib
US Patent App. 17/079,494, 2021
DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision
TM Hsu, YC Wang
arXiv preprint arXiv:2103.08290, 2021
Methods and apparatus for radio frequency sensing in diverse environments
U Ha, J Leng, A Khaddaj, Y Ma, TM Hsu, Z Zhong, F Adib
US Patent 10,872,209, 2020
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