Pendeteksi Mobil Berdasarkan Merek dan Tipe Menggunakan Algoritma YOLO - Al Riansyah; A Haidar Mirza (LPPM UBHINUS MALANG, 2023)
The government system in an area or city has regulations in regulating the activities of its residents, especially those related to driving on the highway. Traffic violations often occur on urban roads and highways, this can trigger accidents due to violating traffic regulations. This has prompted the government to take firm measures against motorists who violate regulations. Therefore we need a system that can help monitor traffic conditions. So, the aims this research is create a system that is able to detect car vehicles based on the brand and type with a high level of detection accuracy, so that it can make it easier to recognize car objects around. The detection system will be developed using the YOLO (You Only Look Once) Algorithm, because YOLO is one of the fastest and most accurate methods of object detection and is even capable of exceeding 2 times the capabilities of other algorithms. The YOLO (You Only Look Once) algorithm is an architecture of Deep Learning and an algorithm developed to detect an object in real-time. Detection is carried out on the image, and when accessing a laptop webcam, which contains a car object, uses a model from a dataset that has been trained using the Darknet framework. The detected car object will have a bounding box in the object area, and there will be a description of the car name and type and year of production in the bounding box area. Based on the classification performance test of the data that has been trained, it shows that the accuracy value reaches 92% so it can be concluded that the system can work well.