• Sarah Muskan
• Dr Jalesh Kumar

The object detection task entails locating and identifying certain objects on a picture and classifies them. It is the capacity of software systems to identify objects in an image or a video. Various technologies use object detection such as detection of faces and vehicles, security systems, driverless cars etc. Real-time processing is designed using an object detection system technology called YOLO(You Only Look Once). It has several advantages when compared to that of other object detection methods. Various algorithms like Convolutional Neural Network and Fast Convolutional Neural Network, do not look at the image completely, but Yolo does. In this dissertation, it is proposed that the model predicts the objects by drawing bounding boxes around them using convolution networks and detects the objects faster compared to other algorithms.

YOLO, Image, Video, Real-Time.

"Object Detection Using YOLO Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.b499-b503, September-2022, Available :http://www.jetir.org/papers/JETIR2209160.pdf

"Object Detection Using YOLO Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppb499-b503, September-2022, Available at : http://www.jetir.org/papers/JETIR2209160.pdf