Face Mask Detection Using MobileNetV2

Built a deep learning model using MobileNetV2 to detect face masks, a crucial tool for public safety during the COVID-19 pandemic. Achieved a 97.71% accuracy on the test dataset, demonstrating the model’s robustness and efficiency under varying conditions.

The project showcases expertise in applying deep learning techniques for real-time image analysis and classification, contributing to public health and safety efforts.