| On the class imbalance problem X Guo, Y Yin, C Dong, G Yang, GT Zhou Proceedings of ICNC'08 4, 192-201, 2008 | 653 | 2008 |
| Learning structured inference neural networks with label relations H Hu, GT Zhou, Z Deng, Z Liao, G Mori Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 159 | 2016 |
| Mass estimation and its applications KM Ting, GT Zhou, FT Liu, JSC Tan Proceedings of KDD'10, 989-998, 2010 | 79 | 2010 |
| Context-aware feature embedding and anomaly detection of sequential log data using deep recurrent neural networks H Hajimirsadeghi, GT Zhou, A Brownsword, N Agarwal, P Chandrashekar, ... US Patent 11,218,498, 2022 | 63 | 2022 |
| Mass estimation KM Ting, GT Zhou, FT Liu, SC Tan Machine learning 90, 127-160, 2013 | 58 | 2013 |
| K-means based fingerprint segmentation with sensor interoperability G Yang, GT Zhou, Y Yin, X Yang EURASIP Journal on Advances in Signal Processing, 1-12, 2010 | 42 | 2010 |
| Relevance feature mapping for content-based multimedia information retrieval GT Zhou, KM Ting, FT Liu, Y Yin Pattern Recognition 45, 1707-1720, 2012 | 36 | 2012 |
| Latent maximum margin clustering GT Zhou, T Lan, A Vahdat, G Mori Advances in neural information processing systems 26, 2013 | 32 | 2013 |
| Malicious activity detection by cross-trace analysis and deep learning GT Zhou, H Hajimirsadeghi, A Brownsword, S Wray, C Schelp, ... US Patent 11,451,565, 2022 | 29 | 2022 |
| Discovering human interactions in videos with limited data labeling M Khodabandeh, A Vahdat, GT Zhou, H Hajimirsadeghi, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 28 | 2015 |
| Malicious activity detection by cross-trace analysis and deep learning JF Peinador, MF Gomez, GT Zhou, H Hajimirsadeghi, A Brownsword, ... US Patent 11,082,438, 2021 | 22 | 2021 |
| Structured label inference for visual understanding N Nauata, H Hu, GT Zhou, Z Deng, Z Liao, G Mori IEEE transactions on pattern analysis and machine intelligence 42 (5), 1257-1271, 2019 | 22 | 2019 |
| Labelbank: Revisiting global perspectives for semantic segmentation H Hu, Z Deng, GT Zhou, F Sha, G Mori arXiv preprint arXiv:1703.09891, 2017 | 21 | 2017 |
| Learning action primitives for multi-level video event understanding T Lan, L Chen, Z Deng, GT Zhou, G Mori Computer Vision-ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and …, 2015 | 15 | 2015 |
| Time perception machine: Temporal point processes for the when, where and what of activity prediction Y Zhong, B Xu, GT Zhou, L Bornn, G Mori arXiv preprint arXiv:1808.04063, 2018 | 14 | 2018 |
| Discovering video clusters from visual features and noisy tags A Vahdat, GT Zhou, G Mori Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 14 | 2014 |
| Learning class-to-image distance with object matchings GT Zhou, T Lan, W Yang, G Mori Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 8 | 2013 |
| Technique for validating a prognostic-surveillance mechanism in an enterprise computer system KC Gross, K Vaidyanathan, GT Zhou US Patent 10,540,612, 2020 | 6 | 2020 |
| Recalling holistic information for semantic segmentation H Hu, Z Deng, GT Zhou, F Sha, G Mori arXiv preprint arXiv:1611.08061, 2016 | 5 | 2016 |
| On Co-Training Style Algorithms C Dong, Y Yin, X Guo, G Yang, GT Zhou Proceedings of ICNC'08 7, 196-201, 2008 | 5 | 2008 |
Greg MoriResearch Director, Borealis AI; Professor, School of Computing Science, Simon Fraser UniversityVerified email at cs.sfu.ca
