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Research On Vehicle Detection Based On Improved YOLOv8 by Ceresskhr is a document available to read on EtoBox.

This document presents an improved vehicle detection method based on the YOLOv8 network, incorporating FasterNet as the backbone, the CBAM attention mechanism, and a modified loss function to enhance detection accuracy and speed. Experimental results indicate significant improvements in detection accuracy for cars, persons, and motorcycles, achieving 98.3%, 89.1%, and 88.4% respectively, along with enhanced performance metrics compared to previous models. Future work aims to address challenges in complex en

Author

Ceresskhr

Language

EN