Abstract
Facial recognition is a fast-growing area used widely in identity verification, monitoring, and access control systems. High recognition rate and less training time are key factors in facial recognition problem. In our paper, we have compared artificial neural network (ANN) and convolutional neural network (CNN) for this specified problem. Our dataset contains more than 14,855 images out of which 1325 images with varied expressions and backgrounds are of the subject to be recognized. Results show the supremacy of CNN over ANN in terms of accuracy in facial recognition and less number of epochs, i.e. lesser training time.
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Singh, N.S., Hariharan, S., Gupta, M. (2020). Facial Recognition Using Deep Learning. In: Jain, V., Chaudhary, G., Taplamacioglu, M., Agarwal, M. (eds) Advances in Data Sciences, Security and Applications. Lecture Notes in Electrical Engineering, vol 612. Springer, Singapore. https://doi.org/10.1007/978-981-15-0372-6_30
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DOI: https://doi.org/10.1007/978-981-15-0372-6_30
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Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-0371-9
Online ISBN: 978-981-15-0372-6
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