The paper reports a new model based on the understanding and encompassing intelligence from brain i.e. biological pyramidal neurons, tailored for emotion recognition. Our objective is to introduce and utilize usage of non-Convolutional layers in models and show comparable or state-of-the-art performance for multi-class emotion recognition problem. We open-sourced the optimized code for researchers. Our model shows state-of-the-art performance on two emotion recognition datasets (eNTERFACE and Youtube) enhancing previous best result by 9.47%9.47% and 20.8 .8%, respectively.
EmoP3D: A brain like pyramidal deep neural network for emotion recognition / E. Di Nardo, A. Petrosino, I. Ullah (LECTURE NOTES IN ARTIFICIAL INTELLIGENCE). - In: ECCV 2018: Computer Vision – ECCV 2018 Workshops / [a cura di] L. Leal-Taixé, S. Roth. - Ebook. - [s.l] : Springer Verlag, 2019. - ISBN 9783030110147. - pp. 607-616 (( convegno ECCV tenutosi a Munich nel 2018 [10.1007/978-3-030-11015-4_46].
EmoP3D: A brain like pyramidal deep neural network for emotion recognition
E. Di Nardo
Primo
;I. UllahUltimo
2019
Abstract
The paper reports a new model based on the understanding and encompassing intelligence from brain i.e. biological pyramidal neurons, tailored for emotion recognition. Our objective is to introduce and utilize usage of non-Convolutional layers in models and show comparable or state-of-the-art performance for multi-class emotion recognition problem. We open-sourced the optimized code for researchers. Our model shows state-of-the-art performance on two emotion recognition datasets (eNTERFACE and Youtube) enhancing previous best result by 9.47%9.47% and 20.8 .8%, respectively.
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