ResMoNet: A Residual Mobile-based Network for Facial Emotion Recognition in Resource-Limited Systems

15 May 2020Rodolfo Ferro-PérezHugo Mitre-Hernandez

The Deep Neural Networks (DNNs) models have contributed a high accuracy for the classification of human emotional states from facial expression recognition data sets, where efficiency is an important factor for resource-limited systems as mobile devices and embedded systems. There are efficient Convolutional Neural Networks (CNN) models as MobileNet, PeleeNet, Extended Deep Neural Network (EDNN) and Inception-Based Deep Neural Network (IDNN) in terms of model architecture results: parameters, Floating-point OPerations (FLOPs) and accuracy... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper