Object Detection Using YOLO Algorithm
The YOLO algorithm model detects and recognizes the objects, and the improved model will examine the entire image and split the image into regions and maps the confidence probability using a neural network on the image.
Abstract
The aim of this study is to find a stable system that can detect the object in fraction of seconds from different sources like image, surveillances, bus, car etc. There are different types of algorithms to find the object with the help of frame. This study is to recognize the object classification and localization. The trained weights should have the maximum confident level possible when classifying objects from external events or detecting multiple objects from an image. To detect the object in the existing system, we use to split the image into different class and focus on the specific region or the subject in the frame. Our proposal using the YOLO algorithm model detects and recognizes the objects, and the improved model will examine the entire image. The YOLO model splits the image into regions and maps the confidence probability using a neural network on the image.