Browsing by Author "Donmez, Hayriye"

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    A Novel Face Identification Implementation for Class Attendance Monitoring
    (Institute of Electrical and Electronics Engineers Inc., 2019) Hayriye Donmez; Sena Yagmur Sen; Nedim Orta; Atakan Aylanc; Ibrahim Zincir; Donmez, Hayriye; Sen, Sena Yagmur; Zincir, Ibrahim; Orta, Nedim; Aylanc, Atakan
    Face identification has become more significant and relevant in the recent years. It is widely used for security purposes in enterprises and state-owned business since it has many advantages and benefits compared to other state of the art security applications. Previous face identification implementations inherited many different approaches and algorithms in order to overcome the challenges of recognizing an individual from a variety of angles and heights but none of them were completely successful. The main goal of this research is to demonstrate a novel face identification framework for an autonomous class attendance monitoring system implementing SIFT (Scale Invariant Feature Transform) algorithm. An image dataset generated with the participation of 20 volunteers that were photographed from a variety of different angles and heights was tested with the proposed system and achieved successful results in general with reasonable accuracy rates. © 2020 Elsevier B.V. All rights reserved.
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    Citation - WoS: 21
    Citation - Scopus: 48
    Emotion Classification from EEG Signals in Convolutional Neural Networks
    (IEEE, 2019) Hayriye Donmez; Nalan Ozkurt; Donmez, Hayriye; Ozkurt, Nalan
    The objective of this research is to classify EEG (electroencephalography) signal recordings of the subjects evoked by visual stimulus by using CNN (Convolutional Neural Networks). EEG records the electrical activity of brain signals. In medicine EEG is used to diagnose some neurological disorders but moreover the classification of the emotions is also possible from EEG recordings. Emotion recognition is an important task for the computers in machine perception. Therefore in this study the participants are presented with a video containing funny scary and sad excerpts and simultaneously EEG signal is measured by Neurosky Mindwave EEG Headset. The spectrogram of EEG signals is supplied to CNN and three emotions are classified using brain signal spectrogram images.