Leveraging Monte Carlo Dropout for Uncertainty Quantification in Real-Time Object Detection of Autonomous Vehicles

With the recent advancements in machine learning technology, the accuracy of autonomous driving object detection models has significantly improved. However, due to the complexity and variability of real-world traffic scenarios, such as extreme weather conditions, unconventional lighting, and unknown...

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Номзүйн дэлгэрэнгүй

Үндсэн зохиолчид:	Rui Zhao, Kui Wang, Yang Xiao, Fei Gao, Zhenhai Gao
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	IEEE 2024-01-01
Цуврал:	IEEE Access
Нөхцлүүд:	Uncertainty quantification object detection autonomous vehicles YOLOv5 Monte Carlo dropout
Онлайн хандалт:	https://ieeexplore.ieee.org/document/10401930/
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!