A Review on Improving Traffic-Sign Detection Using Yolo Algo | 90585
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A Review on Improving Traffic-Sign Detection Using Yolo Algorithm for Object Detection.


Rai Shalini Sunil Kumar* and Professor Tejas S Patel

The Traffic sign detection and recognition plays a vital role in road transport systems. Traffic Sign Recognition could be a driver help feature that may be used to notify and warn the driver by displaying restrictions that may exist on the outstretch of the road. Examples of such ordinances are “stop-light” or “zebra crossing " signs. The YOLO algorithm uses convolutional neural networks (CNN) to detect objects for real-time detection. The algorithm only requires a single forward propagation through a neural network to detect objects. This means that the prediction of the entire image is done in a single execution of the algorithm. Thus, here the proposed work will use the YOLO algorithm to detect the object in an improved way of the existing technique. 

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