Open AccessAn Efficient and Accurate Real Time Facial Expression Detection Using CNN
Author(s) -
Bommagani Srujana,
M. Sree Devi
Publication year - 2021
Publication title -
psychology
Language(s) - English
Resource type - Journals
ISSN - 0033-3077
DOI - 10.17762/pae.v58i2.1962
Subject(s) - facial expression , convolutional neural network , psychology , expression (computer science) , feeling , comprehension , facial expression recognition , cognitive psychology , mainstream , audit , computer science , artificial intelligence , facial recognition system , communication , social psychology , pattern recognition (psychology) , programming language , philosophy , theology , management , economics
Real Facial expression acknowledgment (RTFER) has become a functioning examination zone that finds a ton of utilizations in territories like human-PC interfaces, human feeling investigation, mental investigation, clinical conclusion and so on Mainstream strategies utilized for this intention depend on math and appearance. Profound convolutional neural networks (CNN) have appeared to beat customary strategies in different visual acknowledgment errands including Facial Expression Recognition. Despite the fact that endeavours are made to improve the exactness of RTFER frameworks utilizing CNN, for functional applications existing strategies probably won't be adequate. This examination incorporates a conventional audit of RTFER frameworks utilizing CNN and their qualities and restrictions which assist us with comprehension and improve the RTFER frameworks further.