Facial Emotion Recognition using Deep Learning
Ch.Kousalya1, G.Sripoorna2, Y.Keerthi Tejaswi3, G.Pradeepini4
1G.Pradeepini, Ph.D, Professor, CSE Department, KL University Guntur, Andhra Pradesh, India.
2Ch.Kouslaya, Computer Science and Engineering, KL University, Guntur, AndhraPradesh ,India.
3G.Sripoorna, Computer Science and Engineering, KL University, Guntur, AndhraPradesh ,India.
4Y.Keerthi Tejaswi, Computer Science and Engineering, KL University, Guntur, AndhraPradesh ,India.
Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 10061-10064 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9521118419/2019©BEIESP | DOI: 10.35940/ijrte.D9521.118419
Open Access | Ethics and Policies | Cite  | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Face Emotion Recognition (FER), the human face assumes a significant job in programmed acknowledgment of feelings in the field of recognizing human feelings and the cooperation among humans and PC for some genuine applications. The greater part of the revealed facial feeling acknowledgment frameworks aren’t completely viewed as subject free unique highlights thus they are not hearty enough for reality. The feelings are successfully variable happenings that are evoked because of affecting power. In this way, all things considered, applications, recognition of feeling is an extremely testing assignment.
Keywords: Holistic Component, Viola-Jones, Gabor Feature, Convolutional neural system.
Scope of the Article: Deep Learning.