Facial Expression Recognition using Transfer Learning

Soodamani Ramalingam; Fabio Garcia

doi:10.1109/CCST.2018.8585504

Facial Expression Recognition using Transfer Learning

Soodamani Ramalingam, Fabio Garcia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

303 Downloads (Pure)

Abstract

In this paper, we investigate Deep Learning architectures for the recognition of facial expressions. In particular, we consider the concept of Transfer Learning whereby features learnt from generic images of large scale datasets can be used to train models of smaller databases without losing the generalization ability.

Original language	English
Title of host publication	2018 International Carnahan Conference on Security Technology (ICCST) Proceedings
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	5
ISBN (Electronic)	9781538679319
ISBN (Print)	9781538679326
DOIs	https://doi.org/10.1109/CCST.2018.8585504
Publication status	Published - 24 Dec 2018
Event	52nd Annual ICCST - 2018 International Carnahan Conference on Security Technology (ICCST) - Montreal, Quebec, Canada, Montreal, Canada Duration: 22 Oct 2018 → 25 Oct 2018 https://site.ieee.org/iccst/2018-montreal-canada/

Conference

Conference	52nd Annual ICCST - 2018 International Carnahan Conference on Security Technology (ICCST)
Abbreviated title	IEEE ICCST 2018
Country/Territory	Canada
City	Montreal
Period	22/10/18 → 25/10/18
Internet address	https://site.ieee.org/iccst/2018-montreal-canada/

Keywords

Facial Expression Recognition
Deep Learning

Access to Document

10.1109/CCST.2018.8585504Licence: Unspecified

accepted-version
© 2021 IEEE - All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1109/CCST.2018.8585504
Accepted author manuscript, 294 KBLicence: Unspecified

Cite this

@inproceedings{07993f7aeacc4d6e8a55358df4d7dda3,

title = "Facial Expression Recognition using Transfer Learning",

abstract = "In this paper, we investigate Deep Learning architectures for the recognition of facial expressions. In particular, we consider the concept of Transfer Learning whereby features learnt from generic images of large scale datasets can be used to train models of smaller databases without losing the generalization ability.",

keywords = "Facial Expression Recognition, Deep Learning",

author = "Soodamani Ramalingam and Fabio Garcia",

note = "{\textcopyright} 2021 IEEE - All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1109/CCST.2018.8585504; 52nd Annual ICCST - 2018 International Carnahan Conference on Security Technology (ICCST), IEEE ICCST 2018 ; Conference date: 22-10-2018 Through 25-10-2018",

year = "2018",

month = dec,

day = "24",

doi = "10.1109/CCST.2018.8585504",

language = "English",

isbn = "9781538679326",

booktitle = "2018 International Carnahan Conference on Security Technology (ICCST) Proceedings",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

url = "https://site.ieee.org/iccst/2018-montreal-canada/",

}

Ramalingam, S & Garcia, F 2018, Facial Expression Recognition using Transfer Learning. in 2018 International Carnahan Conference on Security Technology (ICCST) Proceedings. Institute of Electrical and Electronics Engineers (IEEE), 52nd Annual ICCST - 2018 International Carnahan Conference on Security Technology (ICCST), Montreal, Quebec, Canada, 22/10/18. https://doi.org/10.1109/CCST.2018.8585504

TY - GEN

T1 - Facial Expression Recognition using Transfer Learning

AU - Ramalingam, Soodamani

AU - Garcia, Fabio

PY - 2018/12/24

Y1 - 2018/12/24

N2 - In this paper, we investigate Deep Learning architectures for the recognition of facial expressions. In particular, we consider the concept of Transfer Learning whereby features learnt from generic images of large scale datasets can be used to train models of smaller databases without losing the generalization ability.

AB - In this paper, we investigate Deep Learning architectures for the recognition of facial expressions. In particular, we consider the concept of Transfer Learning whereby features learnt from generic images of large scale datasets can be used to train models of smaller databases without losing the generalization ability.

KW - Facial Expression Recognition

KW - Deep Learning

U2 - 10.1109/CCST.2018.8585504

DO - 10.1109/CCST.2018.8585504

M3 - Conference contribution

SN - 9781538679326

BT - 2018 International Carnahan Conference on Security Technology (ICCST) Proceedings

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 52nd Annual ICCST - 2018 International Carnahan Conference on Security Technology (ICCST)

Y2 - 22 October 2018 through 25 October 2018

ER -

Facial Expression Recognition using Transfer Learning

Abstract

Conference

Keywords

Access to Document

Fingerprint

Cite this