Improved YOLOv4-tiny network for real-time electronic component detection
Abstract In the electronics industry environment, rapid recognition of objects to be grasped from digital images is essential for visual guidance of intelligent robots. However, electronic components have a small size, are difficult to distinguish, and are in motion on a conveyor belt, making target...
Guardado en:
Autores principales: | Ce Guo, Xiao-ling Lv, Yan Zhang, Ming-lu Zhang |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/764eb43b9594409eb2bf5c2baf253dcf |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Real-time detection of particleboard surface defects based on improved YOLOV5 target detection
por: Ziyu Zhao, et al.
Publicado: (2021) -
Real‐time automatic helmet detection of motorcyclists in urban traffic using improved YOLOv5 detector
por: Wei Jia, et al.
Publicado: (2021) -
Ginger Seeding Detection and Shoot Orientation Discrimination Using an Improved YOLOv4-LITE Network
por: Lifa Fang, et al.
Publicado: (2021) -
Object Detection Method for Grasping Robot Based on Improved YOLOv5
por: Qisong Song, et al.
Publicado: (2021) -
Tomato detection based on modified YOLOv3 framework
por: Mubashiru Olarewaju Lawal
Publicado: (2021)