Feed Forward Neural Network – Facial Expression Recognition Using 2D Image Texture

Authors: Wisam A. Qader1 & Saman Mirza Abdullah2 & Musa M. Ameen3 & Muhammed S. Anwar4
1Information Technology Department, Faculty of Science, Tishk International University, Erbil, Iraq
2Software Engineering Department, Koya University, Erbil, Iraq
3Computer Engineering Department, Faculty of Engineering, Tishk International University, Erbil, Iraq
4Computer Engineering Department, Faculty of Engineering, Tishk International University, Erbil, Iraq

Abstract: Facial Expression Recognition (FER) is a very active field of study in a wide range of fields such as computer vision, human emotional analyses، pattern recognition and AI. FER has received extensive awareness because it can be employed in human computer interaction (HCI), human emotional analyses, interactive video, image indexing and retrieval. Human facial expression Recognition is one of the most powerful and difficult responsibilities of social communication. Face expressions are, in general terms, natural and direct methods of communicating emotions and intentions for human beings. GWT is applied as a preprocess stage. For the classification of face expressions, this study employs the well-known Feed Forward Propagating Algorithm to create and train a neural network.

Keywords: Feature Extraction, FER (Face Expression Recognition), Classification, GWT

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Doi: 10.23918/eajse.v8i1p216

Published: August 15, 2022


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