| Learning features for offline handwritten signature verification using deep convolutional neural networks LG Hafemann, R Sabourin, LS Oliveira Pattern Recognition 70, 163-176, 2017 | 343 | 2017 |
| Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses J Rony, LG Hafemann, LS Oliveira, IB Ayed, R Sabourin, E Granger arXiv preprint arXiv:1811.09600, 2018 | 297 | 2018 |
| Offline handwritten signature verification—literature review LG Hafemann, R Sabourin, LS Oliveira 2017 seventh international conference on image processing theory, tools and …, 2017 | 285 | 2017 |
| Writer-independent feature learning for offline signature verification using deep convolutional neural networks LG Hafemann, R Sabourin, LS Oliveira 2016 international joint conference on neural networks (IJCNN), 2576-2583, 2016 | 164 | 2016 |
| Forest species recognition using deep convolutional neural networks LG Hafemann, LS Oliveira, P Cavalin 2014 22Nd international conference on pattern recognition, 1103-1107, 2014 | 143 | 2014 |
| DESlib: A Dynamic ensemble selection library in Python RMO Cruz, LG Hafemann, R Sabourin, GDC Cavalcanti The Journal of Machine Learning Research 21 (1), 283-287, 2020 | 87 | 2020 |
| Analyzing features learned for offline signature verification using deep CNNs LG Hafemann, R Sabourin, LS Oliveira 2016 23rd international conference on pattern recognition (ICPR), 2989-2994, 2016 | 83 | 2016 |
| Fixed-sized representation learning from offline handwritten signatures of different sizes LG Hafemann, LS Oliveira, R Sabourin International Journal on Document Analysis and Recognition (IJDAR) 21, 219-232, 2018 | 81 | 2018 |
| Universal adversarial audio perturbations S Abdoli, LG Hafemann, J Rony, IB Ayed, P Cardinal, AL Koerich arXiv preprint arXiv:1908.03173, 2019 | 49 | 2019 |
| Characterizing and evaluating adversarial examples for offline handwritten signature verification LG Hafemann, R Sabourin, LS Oliveira IEEE Transactions on Information Forensics and Security 14 (8), 2153-2166, 2019 | 46 | 2019 |
| Transfer learning between texture classification tasks using convolutional neural networks LG Hafemann, LS Oliveira, PR Cavalin, R Sabourin 2015 International Joint Conference on Neural Networks (IJCNN), 1-7, 2015 | 42 | 2015 |
| Group activity detection from trajectory and video data in soccer R Sanford, S Gorji, LG Hafemann, B Pourbabaee, M Javan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 35 | 2020 |
| Meta-learning for fast classifier adaptation to new users of signature verification systems LG Hafemann, R Sabourin, LS Oliveira IEEE Transactions on Information Forensics and Security 15, 1735-1745, 2019 | 26 | 2019 |
| Adversarial vision challenge W Brendel, J Rauber, A Kurakin, N Papernot, B Veliqi, SP Mohanty, ... The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020 | 23 | 2020 |
| An analysis of deep neural networks for texture classification LG Hafemann Federal University Of Paraná, 2014 | 16 | 2014 |
| Detecting and matching related objects with one proposal multiple predictions Y Liu, LG Hafemann, M Jamieson, M Javan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 7 | 2021 |
| A Scale-Invariant Trajectory Simplification Method for Efficient Data Collection in Videos Y Liu, LG Hafemann Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | | 2023 |
| Learning features for offline handwritten signature verification LG Hafemann École de technologie supérieure, 2019 | | 2019 |
| Offline Handwritten Signature Verification LG Hafemann, R Sabourin, LS Oliveira arXiv preprint arXiv:1507.07909, 2015 | | 2015 |
| Maximizing the Minimum Achievable Secrecy Rate for a Two-User Gaussian Weak Interference Channel............ M Kaminaga, T Suzuki, M Fukase, R Richter, C Gottschlich, L Mentch, ... | | |
Robert SabourinProfessor emeritus @ École de technologie supérieure - LIVIA - REPARTIVahvistettu sähköpostiosoite verkkotunnuksessa etsmtl.ca
