YOLOv8-SCS: Improved Object Detection for Autonomous Driving Under Adverse Weather Conditions

Adverse weather conditions significantly impact the performance of autonomous driving object detection systems, leading to reduced detection accuracy and an increased false detection rate. Limited annotated data further restricts performance improvement. Hence, improving detection performance under...

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מידע ביבליוגרפי

Principais autores:	Younggyu Lee, Jinho Kang
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	IEEE 2025-01-01
סדרה:	IEEE Access
נושאים:	Autonomous driving adverse weather machine learning deep neural network object detection YOLOv8
גישה מקוונת:	https://ieeexplore.ieee.org/document/11135491/
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!