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FExR.A-DCNN: Facial Emotion Recognition with Attention mechanism using Deep Convolution Neural Network

Published: 24 October 2022 Publication History

Abstract

Human Facial Emotions play an important role in non-verbal communication between people. Automated Facial Recognition can have various impacts on our technology, helping us to better understand human behaviour, detect mental disorders, and synthesising facial expressions. Methods based on appearance and geometry are predominantly used, but fail to achieve high accuracy with limited data-sets. In this article we proposed various techniques using deep learning concepts of CNN to identify 7 key human emotions. We achieved 98% accuracy on CK+ data set having low sample count in 100 epochs, which confirms the superiority of the model in detecting and focusing on key global features for Facial Emotion Recognition.

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Cited By

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  • (2023)AB-DeepLabv3+: An Encoder-Decoder Method with Attention Mechanism for Polyp SegmentationProceedings of the 2023 Fifteenth International Conference on Contemporary Computing10.1145/3607947.3607997(262-268)Online publication date: 3-Aug-2023
  • (2023)Multi-Layer Feature Fusion-based Deep Multi-layer Depth Separable Convolution Neural Network for Alzheimer's Disease Detection2023 International Conference on IoT, Communication and Automation Technology (ICICAT)10.1109/ICICAT57735.2023.10263657(1-5)Online publication date: 23-Jun-2023

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cover image ACM Other conferences
IC3-2022: Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing
August 2022
710 pages
ISBN:9781450396752
DOI:10.1145/3549206
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 October 2022

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Author Tags

  1. Attention Mechanism
  2. Convoluted Neural Network
  3. Convolutional Neural Networks (CNN)
  4. Emotion Recognition(ER)
  5. Facial ER(FER)
  6. Facial Expression Recognition(FExR)
  7. Feature Extraction (FE)

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  • Refereed limited

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Cited By

View all
  • (2023)AB-DeepLabv3+: An Encoder-Decoder Method with Attention Mechanism for Polyp SegmentationProceedings of the 2023 Fifteenth International Conference on Contemporary Computing10.1145/3607947.3607997(262-268)Online publication date: 3-Aug-2023
  • (2023)Multi-Layer Feature Fusion-based Deep Multi-layer Depth Separable Convolution Neural Network for Alzheimer's Disease Detection2023 International Conference on IoT, Communication and Automation Technology (ICICAT)10.1109/ICICAT57735.2023.10263657(1-5)Online publication date: 23-Jun-2023

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