aspg-3-718-1791417426 20261007235706 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2021 4 1 Aman Jain Information Technology Bharati Vidyapeeth’s College Of Engineering, New Delhi, India Jatin Gupta Information Technology Bharati Vidyapeeth’s College Of Engineering, New Delhi, India Somya Khandelwal Information Technology Bharati Vidyapeeth’s College Of Engineering, New Delhi, India Surinder Kaur Information Technology Bharati Vidyapeeth’s College Of Engineering, New Delhi, India One of the most significant parts of integrating computer technologies into intelligent transportation systems (ITS) is vehicle license plate recognition (VLPR). In most cases, however, to recognize a license plate successfully, the location of the license plate is to be determined first. Vehicle License Plate Recognition systems are used by law enforcement agencies, traffic management agencies, control agencies, and various government and non-government agencies. VLPR is used in various commercial applications, including electronic toll collecting, personal security, visitor management systems, parking management, and other corporate applications. As a result, calculating the correct positioning of a license plate from a vehicle image is an essential stage of a VLPR system, which substantially impacts the recognition rate and speed of the entire system. In the fields of intelligent transportation systems and image recognition, VLPR is a popular topic. In this research paper, we address the problem of license plate detection using a You Only Look Once (YOLO)-PyTorch deep learning architecture. In this research, we use YOLO version 5 to recognize a single class in an image dataset. 2021 15 21 718 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.040102 https://www.americaspg.com/journal/3/article/718 https://www.americaspg.com/storage/2644.pdf