YOLOv8 on the Road: Next-Level Perception for Autonomous Vehicles
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.
Authors
- M. Bharathi
- T. Aditya Sai Srinivas (ORCID: https://orcid.org/0009-0004-0013-9157)
- P. Ravinder
Institutions
- Narayan Medical College and Hospital (IN)
Publication Details
- Journal
- Journal of Image Processing and Image Restoration.
- Published
- 2024-11-26
- DOI
- https://doi.org/10.48001/joipir.2024.1217-23
- Primary Topic
- Advanced Neural Network Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00