Transfer Learning Using VGG Based on Deep Convolutional Neural Network For Finger-Knuckle-Print Recognition
| dc.contributor.author | Hamidi, Amira | |
| dc.contributor.author | Khemgani, Salma | |
| dc.contributor.author | Bensid, Khled | |
| dc.date.accessioned | 2024-03-12T19:08:53Z | |
| dc.date.available | 2024-03-12T19:08:53Z | |
| dc.date.issued | 2021-05-25 | |
| dc.description.abstract | Transfer learning is an example of Convolutional Neural Network (CNN) method. It based to reusing a pretrained model knowledge for another task. which used for image classification, feature extraction, and clustering problems. In this paper, we used two types of the pre-trained models VGG–16 and VGG-19 with deep convolutional neural network to extract the features of Finger-Knuckle-Print FKP images in order to develop an efficient multimodal identification system. The results obtained in this work show an excellent performance for unimodal and multimodal identification systems. | |
| dc.identifier.isbn | 978-9931-9788-0-0 | |
| dc.identifier.uri | http://dspace.univ-oeb.dz:4000/handle/123456789/18737 | |
| dc.language.iso | en | |
| dc.publisher | University of Oum El Bouaghi | |
| dc.subject | Tansfer learning; convolutional neural network (CNN); VGG-16; VGG-19; finger-knuckle-print (FKP). | |
| dc.title | Transfer Learning Using VGG Based on Deep Convolutional Neural Network For Finger-Knuckle-Print Recognition | |
| dc.type | Article |
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