PROJECT #10
Face Recognition and Emotion Analysis
The face recognition feature uses a specialized Transfer Learning model trained on a dataset of tagged faces. This model leverages pre-trained weights to improve accuracy and shorten the training process.
PROJECT OVERVIEW
The face recognition feature uses a specialized Transfer Learning model trained on a dataset of tagged faces. This model leverages pre-trained weights to improve accuracy and shorten the training process.
An advanced AI application combining face recognition with real-time emotion analysis. Uses deep learning models built with TensorFlow and Keras, integrated with a Django web interface for easy access and management.
KEY FEATURES
Real-time face detection and recognition
Emotion analysis with 7 emotion categories
Transfer learning for accurate results
Training interface for new faces
Live camera feed processing
Firebase integration for data storage
PROJECT METRICS
94%
ACCURACY
RATE
7
EMOTIONS
TYPES
<100ms
LATENCY
TIME
100+
FACES
TRAINED