Kayaoğlu, Bora

Profile URL
https://hdl.handle.net/20.500.11779/2708
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Email Address
kayaoglubo@mef.edu.tr
Main Affiliation
02.05. Department of Electrical and Electronics Engineering
Status
Current Staff
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ORCID ID
0009-0008-7058-2663
Scopus Author ID
58733830700
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WoS Researcher ID
KLC-3927-2024
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1713169673-vesikalik.avif (17.56 KB)
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2023 Innovations in Intelligent Systems and Applications Conference (ASYU)1
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  • Conference Object
    Citation - Scopus: 1
    Cnn-Based Emotion Recognition Using Data Augmentation and Preprocessing Methods
    (Institute of Electrical and Electronics Engineers Inc., 2023) Toktaş, Tolga; Kayaoğlu, Bora; Kırbız, Serap; 02.05. Department of Electrical and Electronics Engineering; 02. Faculty of Engineering; 01. MEF University
    In this paper, a system that recognizes emotion from human faces is designed using Convolutional Neural Networks (CNN). CNN is known to perform well when trained with a large database. The lack of large and balanced publicly available databases that can be used by deep learning methods for emotion recognition is still a challenge. To overcome this problem, the number of data is increased by merging FER+, CK+ and KDEF databases; and preprocessing is applied to the face images in order to reduce the variations in the database. Data augmentation methods are used to reduce the imbalance in the data distribution that still remains despite the increasing number of data in the merged database. The CNN-based method developed using database merging, image preprocessing and data augmentation, achieved emotion recognition with 80% accuracy.