Computer Vision for Detecting Potholes in Asphalt Roads in Real-Time using RC Car
Developed and trained a Convolutional Neural Network (CNN) based on the AlexNet architecture for real-time detection of potholes in asphalt roads, achieving 92.15% accuracy, 91.38% sensitivity, and an F-score of 96.52%. Optimized the model using high-performance GPUs for deployment in real-time systems.
May 1, 2024
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.
Mar 15, 2023