Vehicle Logo Detection Method Based on Improved YOLOv4
A vehicle logo occupies a small proportion of a car and has different shapes. These characteristics bring difficulties to machine-vision-based vehicle logo detection. To improve the accuracy of vehicle logo detection in complex backgrounds, an improved YOLOv4 model was presented. Firstly, the CSPDen...
Main Authors: | Xiaoli Jiang, Kai Sun, Liqun Ma, Zhijian Qu, Chongguang Ren |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-10-01
|
Series: | Electronics |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-9292/11/20/3400 |
Similar Items
-
Multiple Feature Reweight DenseNet for Image Classification
by: Ke Zhang, et al.
Published: (2019-01-01) -
Recognition and Mapping of Landslide Using a Fully Convolutional DenseNet and Influencing Factors
by: Xiao Gao, et al.
Published: (2021-01-01) -
Nutrients deficiency diagnosis of rice crop by weighted average ensemble learning
by: Md. Simul Hasan Talukder, et al.
Published: (2023-08-01) -
Compressed Video Quality Index Based on Saliency-Aware Artifact Detection
by: Liqun Lin, et al.
Published: (2021-09-01) -
Multiclass objects detection algorithm using DarkNet-53 and DenseNet for intelligent vehicles
by: Lina Yang, et al.
Published: (2023-08-01)