A New Deep Model for Detecting Multiple Moving Targets in Real Traffic Scenarios: Machine Vision-Based Vehicles
When performing multiple target detection, it is difficult to detect small and occluded targets in complex traffic scenes. To this end, an improved YOLOv4 detection method is proposed in this work. Firstly, the network structure of the original YOLOv4 is adjusted, and the 4× down-sampling feature ma...
Main Authors: | Xiaowei Xu, Hao Xiong, Liu Zhan, Grzegorz Królczyk, Rafal Stanislawski, Paolo Gardoni, Zhixiong Li |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-05-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/22/10/3742 |
Similar Items
-
Revolutionizing Agriculture: Real-Time Ripe Tomato Detection With the Enhanced Tomato-YOLOv7 System
by: Jun Guo, et al.
Published: (2023-01-01) -
Research on driverless vehicle vision algorithm
by: Liu Xinchao, et al.
Published: (2021-01-01) -
YOLOv8-CB: Dense Pedestrian Detection Algorithm Based on In-Vehicle Camera
by: Qiuli Liu, et al.
Published: (2024-01-01) -
A Lightweight Vehicle-Pedestrian Detection Algorithm Based on Attention Mechanism in Traffic Scenarios
by: Yong Zhang, et al.
Published: (2022-11-01) -
Classification of Malaria Using Object Detection Models
by: Padmini Krishnadas, et al.
Published: (2022-09-01)