| dc.description.abstract |
This research aims to develop a classification system capable of identifying vehicle types on the highway using YOLOv7 (You Only Look Once version 7), a deep learning-based object detection model that can be used for real-time object detection. With the rapid growth of traffic conditions, traffic monitoring and management have become increasingly crucial in reducing congestion and enhancing road safety. The study involves the collection of image data and labeling of various types of vehicles found on the highway. Subsequently, YOLOv7 model training is conducted using the acquired dataset to classify different types of vehicles such as cars, motorcycles, trucks, and buses. The results of this research indicate that YOLOv7 can efficiently classify vehicle types on the highway with a reasonably good accuracy rate, averaging 66% for videos and 81% for image detection.
Keywords : Highway conditions, vehicle monitoring, artificial intelligence, deep learning, You Only Look Once version 7 (YOLOv7).
| en_US |
