Finger vein identification based on transfer learning of AlexNet - Fairuz, Subha; Habaebi, Mohamed Hadi; Elsheikh, Elsheikh Mohamed Ahmed (IEEE, 2018)
Nowadays finger vein-based validation systems are getting extra attraction among other authentication systems due to high security in terms of ensuring data confidentiality. This system works by recognizing patterns from finger vein images and these images are captured using a camera based on near-infrared technology. In this research, we focused finger vein identification system by using our own finger vein dataset, we trained it with transfer learning of AlexNet model and verified by test images. We have done three different experiments with the same dataset but different sizes of data. Therefore, we obtained varied predictability with 95% accuracy from the second experiment.