This paper presents a software based on an innovative Convolutional Neural Network model to recognize the six Ekman's universal emotions from the photos of human faces captured in the wild. The CNN was trained using three different datasets already labeled and merged after making them homogeneous. A comparison among different types of CNN architectures using the Keras framework for Python language is proposed and the evaluation results are presented

Evaluation of Deep Convolutional Neural Network Achitecture for Emotion Recognition in the Wild / Talipu, A.; Generosi, A.; Giraldi, L.; Mengoni, M.. - ELETTRONICO. - (2019), pp. 25-27. (Intervento presentato al convegno IEEE 23rd International Symposium on Consumer Technologies tenutosi a Ancona, Italy nel 19-21 June) [10.1109/ISCE.2019.8900994].

Evaluation of Deep Convolutional Neural Network Achitecture for Emotion Recognition in the Wild

Talipu A.;Generosi A.;Giraldi L.;Mengoni M.
2019-01-01

Abstract

This paper presents a software based on an innovative Convolutional Neural Network model to recognize the six Ekman's universal emotions from the photos of human faces captured in the wild. The CNN was trained using three different datasets already labeled and merged after making them homogeneous. A comparison among different types of CNN architectures using the Keras framework for Python language is proposed and the evaluation results are presented
2019
978-172813570-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/286314
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