Abstract
Object classification is a common problem in artificial intelligence and now it is usually approached by deep learning. In the paper the artificial neural network (ANN) architecture is considered. According to described ANN architecture, the ANN models are trained and tested on a relatively small Color-FERET facial image database under different conditions. The best fine-tuned ANN model provides 94% face recognition accuracy on Color-FERET frontal images and 98% face recognition accuracy within 3 attempts. However, for improving recognition system accuracy large data sets are still necessary preferably consisting of millions of images.
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Sudars, K. Face recognition Face2vec based on deep learning: Small database case. Aut. Control Comp. Sci. 51, 50–54 (2017). https://doi.org/10.3103/S0146411617010072
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DOI: https://doi.org/10.3103/S0146411617010072