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Convolutional Neural Network Hyperparameters optimization for Facial Emotion Recognition

2021-03-2512th International Symposium on Advanced Topics in Electrical Engineering (ATEE) 2021Code Available0· sign in to hype

Adrian Vulpe-Grigorași, Ovidiu Grigore

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Abstract

This paper presents a method of optimizing the hyperparameters of a convolutional neural network in order to increase accuracy in the context of facial emotion recognition. The optimal hyperparameters of the network were determined by generating and training models based on Random Search algorithm applied on a search space defined by discrete values of hyperparameters. The best model resulted was trained and evaluated using FER2013 database, obtaining an accuracy of 72.16%.

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