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

Authors

  • Wisam A. Qader Information Technology Department, Faculty of Science, Tishk International University, Erbil, Iraq
  • Saman Mirza Abdullah Software Engineering Department, Koya University, Erbil, Iraq
  • Musa M. Ameen Computer Engineering Department, Faculty of Engineering, Tishk International University, Erbil, Iraq
  • Muhammed S. Anwar Computer Engineering Department, Faculty of Engineering, Tishk International University, Erbil, Iraq

DOI:

https://doi.org/10.23918/eajse.v8i1p216

Keywords:

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

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.

References

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Published

2022-08-15

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Section

Articles

How to Cite

Qader, W. A., Abdullah, S. M., Ameen, M. M., & Anwar, M. S. (2022). Feed Forward Neural Network – Facial Expression Recognition Using 2D Image Texture. EURASIAN JOURNAL OF SCIENCE AND ENGINEERING, 8(1), 216-224. https://doi.org/10.23918/eajse.v8i1p216

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