Extreme Learning Machine-Based Age-Invariant Face Recognition With Deep Convolutional Descriptors

Leila Boussaad, Aldjia Boucetta
2022 International Journal of Applied Metaheuristic Computing  
The principal intention of this paper is to study face recognition across age progression at two levels: feature extraction and classification. In other words, this work aims to prove the benefit of replacing the Softmax layer of the Deep-Convolutional Neural Networks (CNN) by Extreme Learning Machine (ELM) classifier based on deep features computed from fully-connected layer of pre-trained AlexNet CNN model, in a context of age-invariant face recognition. Experimental results indicate that the
more » ... ELM classifier combined with feature extracted by the pre-trained AlexNet CNN model worked effectively for face recognition across age progression. As significant highest mean accuracy rates are always obtained using ELM classifier. These results are more significant, following a 95% confidence level hypothesis test.
doi:10.4018/ijamc.290540 fatcat:5weiw4k7rjeonaaldt655g3wga