eCite Digital Repository

Facial expression recognition using a multi-level convolutional neural network

Citation

Nguyen, H-D and Yeom, S and Oh, I-S and Kim, K-M and Kim, S-H, Facial expression recognition using a multi-level convolutional neural network, Proceedings from the International Conference on Pattern Recognition and Artificial Intelligence, 14-17 May 2018, Montreal, Canada, pp. 217-221. ISBN 1895193060 (2018) [Refereed Conference Paper]


Preview
PDF
Restricted - Request a copy
9Mb
  

Copyright Statement

Copyright CENPARMI 2018

Abstract

Even though many breakthroughs have been made in image classification, especially in facial expression recognition, this research area is still challenging in terms of wild sampling environment. In this work, we carry out a study of multi-level features in a convolutional neural network for facial expression recognition. Based on our observations, we introduce a model by classification task. Our model was evaluated on the FER2013 dataset and achieved a comparable performance to the current state-of-the-art methods.

Item Details

Item Type:Refereed Conference Paper
Keywords:facial expression recognition in the wild, multi-level convolutional neural networks
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Artificial Intelligence and Image Processing not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Other Information and Communication Services
Objective Field:Information and Communication Services not elsewhere classified
UTAS Author:Yeom, S (Dr Soonja Yeom)
ID Code:126297
Year Published:2018
Deposited By:Information and Communication Technology
Deposited On:2018-06-04
Last Modified:2019-02-25
Downloads:12 View Download Statistics

Repository Staff Only: item control page