Name
Title | ||
|---|---|---|
Learning Features for Offline Handwritten Signature Verification using Deep Convolutional Neural Networks. |
Abstract | ||
|---|---|---|
•We propose formulations for learning features for Offline Signature Verification.•A novel method that uses knowledge of forgeries from a subset of users is proposed.•Learned features are used to train classifiers for other users (without forgeries).•Experiments on GPDS-960 show a large improvement in state-of-the-art.•Results in other 3 datasets show that the features generalize without fine-tuning. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.patcog.2017.05.012 | Pattern Recognition |
Keywords | DocType | Volume |
Signature verification,Convolutional Neural Networks,Feature learning,Deep learning | Journal | 70 |
Issue | ISSN | Citations |
C | 0031-3203 | 33 |
PageRank | References | Authors |
1.00 | 36 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luiz G. Hafemann | 1 | 63 | 3.03 |
| robert sabourin | 2 | 1095 | 73.81 |
| L. S. Oliveira | 3 | 385 | 25.17 |