Project to infere emotional expressions and benchmark datasets by Niklas Wagner, Felix Mätzler, Samed R. Vossberg, Helen Schneider and Svetlana Pavlitska.
TensorFlow-based deep learning model to classify human emotions from facial expressions using the AffectNet dataset. Includes preprocessing, training, evaluation, and prediction tools. Perfect for exploring emotion recognition and transfer learning.
This repository is devoted to the development of the facial emotion recognition (FER) system as a final bachelor project at the TU/e. Realised by Blazej Manczak. Supervisors: Dr. Laura Astola (Accenture) and Dr. Vlado Menkovski (TU/e)
In this repo, I implemented VGGNet, MobileNet and AlexNet and compared their performance on Emotion Detection Task using AffectNet dataset.
Real-time facial emotion recognition system trained on the AffectNet dataset. Uses deep learning and OpenCV to detect and classify 8 different human emotions in live video feeds.
Mobile Messanger Application with Automatic Facial Emotion Classification
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