دورية أكاديمية

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

التفاصيل البيبلوغرافية
العنوان: Feed Forward Neural Network – Facial Expression Recognition Using 2D Image Texture
المؤلفون: Wisam A. Qader, Saman Mirza Abdullah, Musa M. Ameen, Muhammed S. Anwar
المصدر: Eurasian Journal of Science and Engineering, Vol 8, Iss 1, Pp 216-224 (2022)
بيانات النشر: Tishk International University, 2022.
سنة النشر: 2022
المجموعة: LCC:Science
مصطلحات موضوعية: feature extraction, fer (face expression recognition), classification, gwt, Science
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2414-5629
2414-5602
Relation: https://eajse.tiu.edu.iq/index.php/volume-8-issue-1-article-19/; https://doaj.org/toc/2414-5629; https://doaj.org/toc/2414-5602
DOI: 10.23918/eajse.v8i1p216
URL الوصول: https://doaj.org/article/3aa03583cd384bcda7210cbd8e08183d
رقم الأكسشن: edsdoj.3aa03583cd384bcda7210cbd8e08183d
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:24145629
24145602
DOI:10.23918/eajse.v8i1p216