Title
Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data
Abstract
The papers in this special section are aimed at contributions from computational neuroscience and psychology, artificial intelligence, machine learning, and affective computing, challenging and expanding current research on interpretation and estimation of human affective behavior from longitudinal data, i.e., single or multiple modalities captured over extended periods of time allowing efficient representation of behavior and inference in terms of affect and other socio-cognitive dimensions.
Year
DOI
Venue
2021
10.1109/TAFFC.2021.3079535
IEEE Transactions on Affective Computing
DocType
Volume
Issue
Journal
12
3
ISSN
Citations 
PageRank 
1949-3045
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Pablo V. A. Barros111922.02
Stefan Wermter21100151.62
Ognjen Rudovic350627.64
Hatice Gunes4153987.43