Eu Wern Teh
Eu Wern Teh
Computer Science, University of Guelph
Verified email at - Homepage
Cited by
Cited by
Attention Networks for Weakly Supervised Object Localization
EW Teh, M Rochan, Y Wang
British Machine Vision Conference (BMVC), 2016
Proxynca++: Revisiting and revitalizing proxy neighborhood component analysis
EW Teh, T DeVries, GW Taylor
European Conference on Computer Vision, 448-464, 2020
Visual analytics of social networks: mining and visualizing co-authorship networks
CKS Leung, CL Carmichael, EW Teh
International Conference on Foundations of Augmented Cognition, 335-345, 2011
Learning with less data via weakly labeled patch classification in digital pathology
EW Teh, GW Taylor
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 471-475, 2020
Metric Learning for Patch Classification in Digital Pathology
T Eu Wern, T Graham
Strength in diversity: Understanding the impacts of diverse training sets in self-supervised pre-training for histology images
KL Kupferschmidt, EW Teh, GW Taylor
Apparent Age Estimation with Relational Networks
T Eu Wern, Teh and Graham
2019 16th Conference on Computer and Robot Vision (CRV), 2019
Adapting Object Detectors from Images to Weakly Labeled Videos.
O Chanda, EW Teh, M Rochan, Z Guo, Y Wang
British Machine Vision Conference (BMVC), 2017
Object Localization in Weakly Labeled Data Using Regularized Attention Networks.
EW Teh, Z Guo, Y Wang
IEEE Visual Communications and Image Processing (VCIP), 2017
The gist and rist of iterative self-training for semi-supervised segmentation
EW Teh, T DeVries, B Duke, R Jiang, P Aarabi, GW Taylor
2022 19th Conference on Robots and Vision (CRV), 58-66, 2022
Learning with less labels in Digital Pathology via Scribble Supervision from natural images
EW Teh, GW Taylor
arXiv preprint arXiv:2201.02627, 2022
Understanding the impact of image and input resolution on deep digital pathology patch classifiers
EW Teh, GW Taylor
arXiv preprint arXiv:2204.13829, 2022
Embracing Annotation Efficient Learning (AEL) for Digital Pathology and Natural Images
EW Teh
University of Guelph, 2022
Can weak segmentation labels from natural images aid digital pathology-based cancer classification?
EW Teh, GW Taylor
Weakly supervised object localization using attention-based neural networks
EW Teh
British Machine Vision Conference, 2016
Supplementary Information-ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis
EW Teh, T DeVries, GW Taylor
The system can't perform the operation now. Try again later.
Articles 1–16