International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 186 - Issue 8 |
Published: February 2024 |
Authors: Salwa Almoshity, Salema Younus, Sarah Amer Al-Asbaily |
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Salwa Almoshity, Salema Younus, Sarah Amer Al-Asbaily . Face Expressions Recognition by using Deep Learning. International Journal of Computer Applications. 186, 8 (February 2024), 40-44. DOI=10.5120/ijca2024923432
@article{ 10.5120/ijca2024923432, author = { Salwa Almoshity,Salema Younus,Sarah Amer Al-Asbaily }, title = { Face Expressions Recognition by using Deep Learning }, journal = { International Journal of Computer Applications }, year = { 2024 }, volume = { 186 }, number = { 8 }, pages = { 40-44 }, doi = { 10.5120/ijca2024923432 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2024 %A Salwa Almoshity %A Salema Younus %A Sarah Amer Al-Asbaily %T Face Expressions Recognition by using Deep Learning%T %J International Journal of Computer Applications %V 186 %N 8 %P 40-44 %R 10.5120/ijca2024923432 %I Foundation of Computer Science (FCS), NY, USA
Facial expression recognition is a technology that uses biometric features to classify expressions in human faces. This technology plays a significant role in social communication since it conveys a lot of information about people, is considered a sentiment analysis tool, and is able to automatically recognize the seven basic or universal expressions: anger, contempt, disgust, fear, happiness, sadness, and surprise. Deep learning methods boost the learning process and facilitate the data creation task. In this work, the proposed approach used a non-classical technique, Inception-Resnet-v2, to pre-trained deep neural networks (DNNs) on more than a million images from the ImageNet and tested utilizing the face expression database from the Cohn-Kanade (CK+). The system had a loss validation of 0.014668% and attained 100% accuracy.