Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/3638
Title: | Deep Learning Based Facial Emotion Recognition System | Other Titles: | Derin Ögrenme Tabanli Yüz Duygulari Tanima Sistemi | Authors: | Ozdemir M.A. Elagoz B. Alaybeyoglu Soy A. Akan A. |
Keywords: | Deep Learning Emotion Recognition Facial Expression Biomedical engineering Convolutional neural networks Face recognition Learning systems Network architecture Emotional state Ethics committee Facial emotions Facial Expressions Facial images Image preprocessing Learning methods Training accuracy Deep learning |
Publisher: | Institute of Electrical and Electronics Engineers Inc. | Abstract: | In this study, it was aimed to recognize the emotional state from facial images using the deep learning method. In the study, which was approved by the ethics committee, a custom data set was created using videos taken from 20 male and 20 female participants while simulating 7 different facial expressions (happy, sad, surprised, angry, disgusted, scared, and neutral). Firstly, obtained videos were divided into image frames, and then face images were segmented using the Haar library from image frames. The size of the custom data set obtained after the image preprocessing is more than 25 thousand images. The proposed convolutional neural network (CNN) architecture which is mimics of LeNet architecture has been trained with this custom dataset. According to the proposed CNN architecture experiment results, the training loss was found as 0.0115, the training accuracy was found as 99.62%, the validation loss was 0.0109, and the validation accuracy was 99.71%. © 2020 IEEE. | Description: | 2020 Medical Technologies Congress, TIPTEKNO 2020 -- 19 November 2020 through 20 November 2020 -- 166140 | URI: | https://doi.org/10.1109/TIPTEKNO50054.2020.9299256 https://hdl.handle.net/20.500.14365/3638 |
ISBN: | 9.78173E+12 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
Files in This Item:
File | Size | Format | |
---|---|---|---|
2724.pdf Restricted Access | 471.02 kB | Adobe PDF | View/Open Request a copy |
CORE Recommender
SCOPUSTM
Citations
9
checked on Nov 6, 2024
WEB OF SCIENCETM
Citations
2
checked on Nov 6, 2024
Page view(s)
100
checked on Nov 11, 2024
Download(s)
8
checked on Nov 11, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.