Year: 2024
Type: article
Abstract: The system’s products and features drive the product search process. By enhancing low-quality images to high resolution, its performance can be optimized. As machine learning evolves, advanced tools tackle complex features, improving upon legacy systems. This project introduces a new method for detecting vehicles, pedestrians, and traffic signs using publicly available data. We modify the YOLOv8 model to boost accuracy, leveraging its efficiency on mobile devices and minimal RAM usage, with Unity facilitating conversion.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4404865242