Object Detection Using TensorFlow for Road Navigation: Enhancing Safety for the Visually Impaired

Enhanced safety for individuals with visual impairments during driving is achieved through the application of machine learning techniques. Utilizing object identification methods like Faster R-CNN, R-FCN, and SSD, known for their accuracy in real-time applications, our study focuses on training models using diverse datasets, including COCO and KITTI, with the TensorFlow Object Detection API framework. The experiment reveals that SSD algorithms exhibit faster and more accurate object identification, contributing to improved accident prevention for blind individuals. Notably, this technology aids in determining the relative distance between vehicles, providing timely alerts to the user about approaching obstacles.