| Automatic moth detection from trap images for pest management W Ding, G Taylor Computers and Electronics in Agriculture 123, 17-28, 2016 | 319 | 2016 |
| Multimodal and multiscale deep neural networks for the early diagnosis of Alzheimer’s disease using structural MR and FDG-PET images D Lu, K Popuri, GW Ding, R Balachandar, MF Beg Scientific reports 8 (1), 5697, 2018 | 290 | 2018 |
| MMA Training: Direct Input Space Margin Maximization through Adversarial Training GW Ding, Y Sharma, KYC Lui, R Huang International Conference on Learning Representations, 2020 | 221 | 2020 |
| AdverTorch v0. 1: An adversarial robustness toolbox based on pytorch GW Ding, L Wang, X Jin arXiv preprint arXiv:1902.07623, 2019 | 170 | 2019 |
| Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer’s disease D Lu, K Popuri, GW Ding, R Balachandar, MF Beg, ... Medical image analysis 46, 26-34, 2018 | 134* | 2018 |
| Deep-learning based multiclass retinal fluid segmentation and detection in optical coherence tomography images using a fully convolutional neural network D Lu, M Heisler, S Lee, GW Ding, E Navajas, MV Sarunic, MF Beg Medical image analysis 54, 100-110, 2019 | 107 | 2019 |
| On the effectiveness of low frequency perturbations Y Sharma, GW Ding, M Brubaker arXiv preprint arXiv:1903.00073, 2019 | 78 | 2019 |
| Lens-based wavefront sensorless adaptive optics swept source OCT Y Jian, S Lee, MJ Ju, M Heisler, W Ding, RJ Zawadzki, S Bonora, ... Scientific reports 6 (1), 1-10, 2016 | 58 | 2016 |
| Optical mapping of the electrical activity of isolated adult zebrafish hearts: acute effects of temperature E Lin, A Ribeiro, W Ding, L Hove-Madsen, MV Sarunic, MF Beg, ... American Journal of Physiology-Regulatory, Integrative and Comparative …, 2014 | 56 | 2014 |
| Theano-based large-scale visual recognition with multiple gpus W Ding, R Wang, F Mao, G Taylor arXiv preprint arXiv:1412.2302, 2014 | 51 | 2014 |
| On the Sensitivity of Adversarial Robustness to Input Data Distributions GW Ding, KYC Lui, X Jin, L Wang, R Huang International Conference on Learning Representations, 2019 | 50 | 2019 |
| Retinal fluid segmentation and detection in optical coherence tomography images using fully convolutional neural network D Lu, M Heisler, S Lee, G Ding, MV Sarunic, MF Beg arXiv preprint arXiv:1710.04778, 2017 | 40 | 2017 |
| Automatic detection of subretinal fluid and sub-retinal pigment epithelium fluid in optical coherence tomography images W Ding, M Young, S Bourgault, S Lee, DA Albiani, AW Kirker, ... 2013 35th Annual International Conference of the IEEE Engineering in …, 2013 | 33 | 2013 |
| Adversarial robustness of pruned neural networks L Wang, GW Ding, R Huang, Y Cao, YC Lui | 24 | 2018 |
| Alzheimer’s disease neuroimaging I. Multimodal and multiscale deep neural networks for the early diagnosis of Alzheimer’s disease using structural MR and FDG-PET images D Lu, K Popuri, GW Ding, R Balachandar, MF Beg Sci Rep 8 (1), 5697, 2018 | 22 | 2018 |
| Improving GAN training via binarized representation entropy (BRE) regularization Y Cao, GW Ding, KYC Lui, R Huang International Conference on Learning Representations, 2018 | 19 | 2018 |
| LF-UNet–A novel anatomical-aware dual-branch cascaded deep neural network for segmentation of retinal layers and fluid from optical coherence tomography images D Ma, D Lu, S Chen, M Heisler, S Dabiri, S Lee, H Lee, GW Ding, ... Computerized Medical Imaging and Graphics 94, 101988, 2021 | 14 | 2021 |
| Robust pruned neural networks via adversarial training L Wang, W Ding, R Huang, CAO Yanshuai, YC Lui US Patent 11,562,244, 2023 | 13 | 2023 |
| System and method for improved neural network training CAO Yanshuai, YC Lui, W Ding, R Huang US Patent App. 16/172,451, 2019 | 13 | 2019 |
| Cdt: Cascading decision trees for explainable reinforcement learning Z Ding, P Hernandez-Leal, GW Ding, C Li, R Huang arXiv preprint arXiv:2011.07553, 2020 | 11 | 2020 |
Mirza Faisal BegProfessor, Engineering Science, Simon Fraser UniversityVerified email at sfu.ca
