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Comparison Of Facial Emotion Recognition Models Using Deep Learning, Arsany Hanin

University of New Orleans Theses and Dissertations

Facial emotion recognition is a widely studied area with applications in diverse domains such as human-computer interaction, affective computing, and social robotics. This thesis aims to improve the accuracy of facial emotion recognition models by incorporating a second neural network trained on original probabilities and probability transformation, while also comparing the performance of different techniques. The thesis begins with a thorough review of available datasets and technologies used for data collection, highlighting the challenges associated with these datasets. A detailed analysis of various facial emotion detection models, including the baseline model and its different architectures, is presented. The thesis also …