Team
Nevin Toms, Gaurav Tank, Anil Kumar Mondyagu, Sneha Puppala
Categories
Artificial Intelligence, Deep Learning, Python
Overview
The motivation behind our capstone project is to address the critical issue of sidewalk deficiency detection. Sidewalk deficiencies, such as cracks, potholes, and gaps, pose significant risks to pedestrians, leading to trip hazards and accessibility challenges.
In urban environments, the timely detection and repair of these deficiencies are crucial for ensuring pedestrian safety and minimizing accidents. Our objective is to develop an efficient system capable of automatically detecting and segmenting sidewalk deficiencies from images, leveraging deep learning algorithms and computer vision techniques.
Side-walk Deficiency Detection and Segmentation
Side-walk Deficiency Detection and Segmentation using YoloV8.
