mohamed afify afify

"During my academic studies, I led my graduation project focused on Emotion Facial Recognition using Deep Learning techniques. Core Objective: Developed a robust model to detect and classify human emotions from real-time video streams and image datasets. Technical Stack: Utilized Python, OpenCV for image processing, and deep learning frameworks (such as TensorFlow/Keras) to build and train a Convolutional Neural Network (CNN). Data Handling: Pre-processed extensive facial expression datasets, involving image normalization, resizing, and feature extraction to enhance model accuracy. Outcome: Achieved a high-performance model capable of identifying multiple emotional states with significant accuracy, demonstrating the power of AI in human-computer interaction. Key Takeaway: This project sharpened my ability to handle complex, unstructured data and deepened my understanding of model evaluation metrics and performance optimization.