Luiz Gustavo Hafemann
Luiz Gustavo Hafemann
Computer Vision Researcher, Sportlogiq
Verified email at sportlogiq.com - Homepage
Title
Cited by
Cited by
Year
Learning features for offline handwritten signature verification using deep convolutional neural networks
LG Hafemann, R Sabourin, LS Oliveira
Pattern Recognition 70, 163-176, 2017
1862017
Offline handwritten signature verification—literature review
LG Hafemann, R Sabourin, LS Oliveira
2017 Seventh International Conference on Image Processing Theory, Tools and …, 2017
1692017
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
1202016
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
1182018
Forest species recognition using deep convolutional neural networks
LG Hafemann, LS Oliveira, P Cavalin
2014 22Nd international conference on pattern recognition, 1103-1107, 2014
1012014
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
582016
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 (3 …, 2018
442018
DESlib: A Dynamic ensemble selection library in Python.
RMO Cruz, LG Hafemann, R Sabourin, GDC Cavalcanti
J. Mach. Learn. Res. 21 (8), 1-5, 2020
352020
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
282015
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
262019
Universal adversarial audio perturbations
S Abdoli, LG Hafemann, J Rony, IB Ayed, P Cardinal, AL Koerich
arXiv preprint arXiv:1908.03173, 2019
232019
An analysis of deep neural networks for texture classification
LG Hafemann
Federal University Of Paraná, 2014
142014
Adversarial vision challenge
W Brendel, J Rauber, A Kurakin, N Papernot, B Veliqi, SP Mohanty, ...
The NeurIPS'18 Competition, 129-153, 2020
132020
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
92019
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
82020
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
2021
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, ...
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