Results 31 to 40 of about 405,852 (280)

Efficient recognition of facial expressions does not require motor simulation

open access: yeseLife, 2020
What mechanisms underlie facial expression recognition? A popular hypothesis holds that efficient facial expression recognition cannot be achieved by visual analysis alone but additionally requires a mechanism of motor simulation — an unconscious, covert
Gilles Vannuscorps   +2 more
doaj   +1 more source

Robust Lightweight Facial Expression Recognition Network with Label Distribution Training

open access: yesAAAI Conference on Artificial Intelligence, 2021
This paper presents an efficiently robust facial expression recognition (FER) network, named EfficientFace, which holds much fewer parameters but more robust to the FER in the wild.
Zengqun Zhao, Qingshan Liu, Feng Zhou
semanticscholar   +1 more source

Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network [PDF]

open access: yesItalian National Conference on Sensors, 2019
Facial expression recognition has been an active area of research over the past few decades, and it is still challenging due to the high intra-class variation.
Shervin Minaee, AmirAli Abdolrashidi
semanticscholar   +1 more source

Discriminability effect on Garner interference: evidence from recognition of facial identity and expression

open access: yesFrontiers in Psychology, 2013
Using Garner’s speeded classification task existing studies demonstrated an asymmetric interference in the recognition of facial identity and facial expression. It seems that expression is hard to interfere with identity recognition.
Yamin eWang   +3 more
doaj   +1 more source

Facial Expression Recognition in Educational Research From the Perspective of Machine Learning: A Systematic Review

open access: yesIEEE Access, 2023
Facial expression analysis aims to understand human emotions by analyzing visual face information and is a popular topic in the computer vision community. In educational research, the analyzed students’ affect states can be used by faculty members
Bei Fang   +3 more
doaj   +1 more source

Feature Extraction Techniques for Facial Expression Recognition (FER)

open access: yesAl-Iraqia Journal for Scientific Engineering Research, 2023
Facial expression recognition (FER) is a significant area of study in computer vision and affective computing. In numerous applications, such as human-computer interaction, emotion detection, and behavior analysis.
Hadeel Mohammed   +2 more
doaj   +1 more source

Facial expression at retrieval affects recognition of facial identity [PDF]

open access: yesFrontiers in Psychology, 2015
It is well known that memory can be modulated by emotional stimuli at the time of encoding and consolidation. For example, happy faces create better identity recognition than faces with certain other expressions. However, the influence of facial expression at the time of retrieval remains unknown in the literature.
Wenfeng eChen   +8 more
openaire   +3 more sources

Facial Expression Recognition Based on Anti-Aliasing Residual Attention Network [PDF]

open access: yesJisuanji gongcheng, 2023
As it is difficult to extract effective features in facial expression recognition and the high similarity between categories and easy confusion lead to low accuracy of facial expression recognition, a facial expression recognition method based on anti ...
Fangyu FENG, Xiaoshu LUO, Zhiming MENG, Guangyu WANG
doaj   +1 more source

Results: Recognition of Facial Expression by Digital Image Processing [PDF]

open access: yes, 2016
Facial expression is one of most important behavioral measure for studies of emotion, cognitive processes, and social interaction. Facial expression recognition has become a promising research area.
Patil, M. M. (Manjusha)   +1 more
core   +1 more source

Understanding and Mitigating Annotation Bias in Facial Expression Recognition [PDF]

open access: yesIEEE International Conference on Computer Vision, 2021
The performance of a computer vision model depends on the size and quality of its training data. Recent studies have unveiled previously-unknown composition biases in common image datasets which then lead to skewed model outputs, and have proposed ...
Yunliang Chen, Jungseock Joo
semanticscholar   +1 more source

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