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k-Shot Learning for Face Recognition
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 181 - Number 18 |
| Year of Publication: 2018 |
| Authors: Omkar Ranadive, Dhiti Thakkar |
10.5120/ijca2018917871
|
Omkar Ranadive, Dhiti Thakkar . k-Shot Learning for Face Recognition. International Journal of Computer Applications. 181, 18 ( Sep 2018), 43-48. DOI=10.5120/ijca2018917871
Abstract
There have been many recent advancements in the field of artificial intelligence and machine learning. Nevertheless, the problem of learning from a few examples persists. The process of learning from just an example is easy for humans but not for a computer. Learning from a small number of samples is especially necessary in the case of facial recognition systems as the number of samples per person is limited. The aim is to explore, analyze and improve the different techniques which can be used for Face Recognition where the algorithm is fed with a few examples of faces i.e. the process of k shot learning for Face Recognition has been explored using the LFW and FEI datasets. The techniques of transfer learning have been used along with the famous Dlib library with some improvements using methods of deep learning.
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