A Rapid Recognition Method for Electronic Components Based on the Improved YOLO-V3 Network
Rapid object recognition in the industrial field is the key to intelligent manufacturing. The research on fast recognition methods based on deep learning was the focus of researchers in recent years, but the balance between detection speed and accuracy was not well solved. In this paper, a fast reco...
Main Authors: | Rui Huang, Jinan Gu, Xiaohong Sun, Yongtao Hou, Saad Uddin |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-07-01
|
Series: | Electronics |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-9292/8/8/825 |
Similar Items
-
Teacher–Student Behavior Recognition in Classroom Teaching Based on Improved YOLO-v4 and Internet of Things Technology
by: Henghuai Chen, et al.
Published: (2022-12-01) -
Deep Learning Based Traffic Sign Recognition Using YOLO Algorithm
by: Gökalp Çınarer
Published: (2024-01-01) -
A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS
by: Juan Terven, et al.
Published: (2023-11-01) -
Real-Time Counting and Height Measurement of Nursery Seedlings Based on Ghostnet–YoloV4 Network and Binocular Vision Technology
by: Xuguang Yuan, et al.
Published: (2022-09-01) -
Real-Time Pattern-Recognition of GPR Images with YOLO v3 Implemented by Tensorflow
by: Yuanhong Li, et al.
Published: (2020-11-01)