Browsing by Author "Korkmaz, Ilker"

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A Comprehensive Decision Support System for Family Physicians
(Institute of Electrical and Electronics Engineers Inc., 2025) Simsek, Emre; Erkat, Fatma Ezgi; Korkmaz, Ilker; Anagun, Ahmet Sermet
Effect of Age and Gender on Facial Emotion Recognition
(Institute of Electrical and Electronics Engineers Inc., 2020) Oguz K.; Korkmaz I.; Korkmaz B.; Akkaya G.; Alici C.; Kilic E.; Kilic, Ece; Korkmaz, Beyza; Korkmaz, Ilker; Alici, Cem; Akkaya, Guliz; Oguz, Kaya
New research fields and applications on human computer interaction will emerge based on the recognition of emotions on faces. With such aim, our study evaluates the features extracted from faces to recognize emotions. To increase the success rate of these features, we have run several tests to demonstrate how age and gender affect the results. The artificial neural networks were trained by the apparent regions on the face such as eyes, eyebrows, nose, mouth, and jawline and then the networks are tested with different age and gender groups. According to the results, faces of older people have a lower performance rate of emotion recognition. Then, age and gender based groups are created manually, and we show that performance rates of facial emotion recognition have increased for the networks that are trained using these particular groups. © 2020 IEEE.
Navigating the Healthcare Maze through Natural Language: HAAN An AI-Based Health Tool
(Institute of Electrical and Electronics Engineers Inc., 2025) Korkmaz, Ilker; Abdullah Alhammoodi, Tareq M F; Uysal, Hulki Enes; Ozer, Kaan; Erol, Kutluhan
A Shuttle Route Divergence Detection System
(Institute of Electrical and Electronics Engineers Inc., 2020) Korkmaz I.; Ozturk S.D.; Ozturk, Serhat Deniz; Korkmaz, Ilker
Shuttle Route Divergence Detection System is a mobile tracking information system designed for parents to follow the safety of their children who are transported by shuttle buses on regular routes. Main purpose of the system is to provide the parents with a tracking system to monitor their children when they are far away from the home. With the help of the system, the parents will be informed about the location of their children and can early intervene in unusual circumstances. The tracking system developed uses a rule based algorithm to learn and compare the routes with operating data which are written in the database. The system runs in a machine to machine approach using peer to peer communication. The prototype system implemented includes three main devices: parent's PC, child's smartphone, and a management server. Child's mobile phone informs the parent about its location via GPS; parent's computer learns the routes of the shuttle vehicle carrying the child; server provides re-establishment of the data communication between child's and parent's devices. The system is able to warn the parents immediately if the shuttle bus diverges out from any part of the learned route. © 2020 IEEE.