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facial-emotion-detection

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An Android app for real-time facial emotion recognition, designed to improve accuracy for Middle Eastern faces and women wearing hijabs. The CNN model is trained on a hybrid dataset (FER2013, CK+, JAFFE, and IEFDB), achieving 88% accuracy on the hybrid test set and 90% on IEFDB test set.

  • Updated Sep 11, 2023
  • Java

A comprehensive real-time emotion recognition system combining facial and textual analysis with Furhat robot integration for social robotics applications.

  • Updated Feb 6, 2026
  • Jupyter Notebook

A deep learning project that uses a Convolutional Neural Network (CNN) to automatically recognize human facial expressions from images. The model is trained on labeled facial emotion datasets to classify emotions such as happy, sad, angry, surprised, and more with high accuracy.

  • Updated Jun 21, 2025
  • Jupyter Notebook
face-detection-api

Real-time facial emotion detection using optimized CNN architecture achieving ~82% accuracy. Built with TensorFlow/Keras for production deployment with grayscale optimization and data augmentation techniques. Outperforms transfer learning models while maintaining edge-compatible efficiency.

  • Updated Dec 24, 2025
  • HTML

🎭 Detect emotions in real-time from your webcam using DeepFace and OpenCV for instant feedback on feelings like Happy, Sad, and Angry.

  • Updated Jun 21, 2026
  • Python

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