Ozkara C.Ekim P.O.2023-06-162023-06-1620229.78E+12https://doi.org/10.1109/ASYU56188.2022.9925465https://hdl.handle.net/20.500.14365/35112022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022 -- 7 September 2022 through 9 September 2022 -- 183936This project aims to review the most popular deep learning algorithms and their performances in camera systems based on real-time facial emotion recognition and suggest a new model for future applications. Firstly, convolutional neural network (CNN) algorithms that recognize human emotions, such as AlexNet, GoogleNet, and VGG19, are investigated according to their performances. Then, the CNN algorithm with the best numerical performance is chosen for enhancement. After, the new hybrid model is constructed via chosen CNN and long short-term memory (LSTM). Lastly, the proposed model and face images achieved from the camera are combined to simulate real-time application. © 2022 IEEE.eninfo:eu-repo/semantics/closedAccessCNNface detectionfacial expression recognitionhybrid modelLSTMCamerasConvolutional neural networksEmotion RecognitionFace recognitionReal time systemsSpeech recognitionConvolutional neural networkEmotion recognitionFaces detectionFacial emotionsFacial expression recognitionHybrid modelNeural networks algorithmsPerformanceReal- timeVisualization systemLong short-term memoryConference Object10.1109/ASYU56188.2022.99254652-s2.0-85142765138