Abstract
The present study shows the quantitative analysis of the evaluation of traditional methods of facial recognition versus the evaluation of methods based on deep learning, the contribution of this study lies in the conditions of the dataset to be used, which unlike the regular paradigms, it contains a limited size of images to train what the researcher has called a hostile training environment, which will serve as a reference to determine what technique and/or algorithm can work to recognize faces in which you do not have a lot of information to be processed and with a poor quality of the face image to be recognized, factors that in recent years are recurring in the search requests of missing persons or in the absence of the quality of certain security cameras.
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Notes
- 1.
A set of more detailed results can be found in a parallel study conducted by the same author as part of his studies in computer science.
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Rosero Vasquez, S. (2020). Facial Recognition: Traditional Methods vs. Methods Based on Deep Learning. In: Rocha, Á., Ferrás, C., Montenegro Marin, C., Medina García, V. (eds) Information Technology and Systems. ICITS 2020. Advances in Intelligent Systems and Computing, vol 1137. Springer, Cham. https://doi.org/10.1007/978-3-030-40690-5_59
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