• Ms. T .Naga Navya
• Vunnam Harshini
• Tadapaneni Divya Prasanna
• Shaik Farjana
• Malleboyina Deepthi

Real-time object detection is very useful component in real life applications. We use this detection application in many forms .For example using in Automobiles like Autonomous vehicles, Surveillance Systems and robots .These type of applications useful in enhancing the speed of objects in Dynamic environment .To detect them we use Machine learning Algorithms Particularly CNNs .With the help of this Mechanism we can detect the multiple real time applications.to perform any real time object detection methods we need hardware acceleration which further contribute to the ultimate efficiency of the systems. Now a days Real-time object applications has become increasingly vital Across numerous domains .Algorithms we use to prepare these type of Applications provide in depth analysis of state of the art methodologies, including both Traditional machine learning and contemporary machine learning technique Experimental results paving the way for practical Real-time applications .Every model we prepare to detect must be checked before Applying in real life ,we check that by giving numerous images ,text .Finally by training them for the long period object detection application should be able to give Accuracy values.

Real-time object Detection, Convolutional neural network (CNN), Machine learning, Training the object, Optimization.

"REAL TIME OBJECT DETECTION USING YOLO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.373-380, November-2024, Available :http://www.jetir.org/papers/JETIRGO06038.pdf

"REAL TIME OBJECT DETECTION USING YOLO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. pp373-380, November-2024, Available at : http://www.jetir.org/papers/JETIRGO06038.pdf