2020/10/03 by Hafiq Anas, Bacha Rehman, Anas, Hafiq +4
Computer Science · Psychology · #Artificial intelligence #Biology #Competition (biology) #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Convolutional neural network #Data set #Deep learning #Emotion and Mood Recognition #Expression (computer science) #FOS: Computer and information sciences #Face and Expression Recognition #Face recognition and analysis #Facial expression #Facial expression recognition #Facial recognition system #Pattern recognition (psychology) #Set (abstract data type) #cs.CV
paper · pdf · doi:10.48550/arxiv.2010.01301
3 pages, 1 figure
arxiv created 2020/10/03 · openalex publication_date 2020/10/03 · arxiv updated 2020/10/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper describes the proposed methodology, data used and the results of our participation in the ChallengeTrack 2 (Expr Challenge Track) of the Affective Behavior Analysis in-the-wild (ABAW) Competition 2020. In this competition, we have used a proposed deep convolutional neural network (CNN) model to perform automatic facial expression recognition (AFER) on the given dataset. Our proposed model has achieved an accuracy of 50.77% and an F1 score of 29.16% on the validation set.