Research on the Detection Method of Safflower Filaments in Natural Environment Based on Improved YOLOv5s

The accurate and rapid identification of safflower filaments is a prerequisite for automating harvesting. This paper proposes a lightweight, high-precision detection model for safflower filaments based on YOLOv5s, named YOLOv5s-MCD, to address the issues of large existing network model sizes and low...

Celý popis

Podrobná bibliografie

Hlavní autoři:	Bangbang Chen, Feng Ding, Baojian Ma, Xiangdong Liu, Shanping Ning
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2024-01-01
Edice:	IEEE Access
Témata:	Safflower filament natural environment target detection YOLOv5s lightweight
On-line přístup:	https://ieeexplore.ieee.org/document/10580904/
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!