Name
Abstract | ||
|---|---|---|
•A deep-learning based authentication system from inertial signals is proposed.•This framework relies on new transform to make inertial signals rotation invariant.•We propose a robust walking-cycle extraction algorithm with template adaptation.•We combine neural networks with SVM into a new multi-step authentication technique.•An extensive experimental campaign is presented, to validate the proposed system. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.patcog.2017.09.005 | Pattern Recognition |
Keywords | DocType | Volume |
Biometric gait analysis,Target recognition,Classification methods,Convolutional neural networks,Support vector machines,Inertial sensors,Feature extraction,Signal processing,Accelerometer,Gyroscope | Journal | 74 |
Issue | ISSN | Citations |
1 | 0031-3203 | 11 |
PageRank | References | Authors |
0.87 | 28 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matteo Gadaleta | 1 | 28 | 1.72 |
| Michele Rossi | 2 | 228 | 26.33 |