Paper Title
Smart Parking System Using Yolo
Abstract
The paper presents a system that will provide an accurate and reliable way of locating empty parking slots. A
growing interest in creating smart-parking systems has been seen recently in the automotive sector. Accurately detecting and
localizing the parking-slots indicated by regular line segments is a crucial and unresolved problem for such systems. The
vision-based parking-slot recognition is more challenging than it appears due the variety of ground materials, variations in
ambient light, and unexpected shadows generated by neighboring trees, etc. Using computer vision and machine learning
approaches, the work seeks to overcome these challenges. The proposed system will be using YOLO object detection
program. It uses a single neural network with fewer convolution layers and filters in those layers to predict a bounding box
and a confidence score. The system will find empty parking slots and will give a text-based and a speech-based alert
Keywords - Parking Detection, Yolov5, CNN