Oguz K.Korkmaz I.Korkmaz B.Akkaya G.Alici C.Kilic E.2023-06-162023-06-1620209.78E+12https://doi.org/10.1109/ASYU50717.2020.9259854https://hdl.handle.net/20.500.14365/35082020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020 -- 15 October 2020 through 17 October 2020 -- 165305New 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.trinfo:eu-repo/semantics/closedAccessartificial neural networksclassificationfacial emotion recognitionHuman computer interactionIntelligent systemsNeural networksSpeech recognitionEmotion recognitionFacial emotionsOlder PeopleRecognition of emotionResearch fieldsFace recognitionConference Object10.1109/ASYU50717.2020.92598542-s2.0-85097943762