Face Recognition based on Convolutional Neural Network

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Abstract

Recognition holds great significance to give biometric authentications that are utilized in various applications particularly in attendance and security. A gathered database of the subjects is converted applying image processing methods to make this task. This paper suggests a cascade object detector based face detection and convolutional neural network alexnet based face recognition that can recognize the faces. The techniques used for face recognition are machine learning-based methods because of their great precision as associated with different methods. Face detection is the initial level before face recognition that is done utilizing a cascade object detector classifier. Face recognition is performed utilizing Deep Learning's sub-field that is Convolutional Neural Network (CNN). It is a multi-layer network which is used to train the network, to perform a particular task using classification. Check learning of a trained CNN model that is AlexNet is used for face recognition.

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Borra, S. P. R. … Karteek, V. (2020). Face Recognition based on Convolutional Neural Network. International Journal of Engineering and Advanced Technology, 9(4), 192–196. https://doi.org/10.35940/ijeat.d6658.049420

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