Results 21 to 30 of about 8,823 (191)

DS-YOLOv5: A real-time detection and recognition model for helmet wearing

工程科学学报, 2023
Automatic detection and recognition of safety helmet wearing based on video analysis is important to ensure production safety. It is inefficient to supervise whether workers wear safety helmets by manual means.
Peirui BAI, Rui WANG, Qingyi LIU, Chao HAN, Hongxuan DU, Mengyu XUANYUAN, Yingxia FU   +6 more
doaj   +1 more source

Surface Defect Detection Method of Wooden Spoon Based on Improved YOLOv5 Algorithm

BioResources, 2023
The available surface defect detection methods for disposable wooden spoons still involve screening with the naked eye. This detection method is not only inefficient but also accompanied by problems such as false detection and missed detection. Therefore,
Siqing Tian, Xiao Li, Xiaolin Fang, Xiaozhong Qi, Jichao Li   +4 more
doaj  

Research on Detection Method for Tunnel Lining Defects Based on DCAM-YOLOv5 in GPR B-Scan [PDF]

Radioengineering, 2023
This paper presents a detection method of DCAM-YOLOv5 for ground penetrating radar (GPR) to address the difficulty of identifying complex and multi-type defects in tunnel linings.
D. Chen, S. Xiong, L. Guo
doaj  

Coal gangue detection based on CBA-YOLO model

Gong-kuang zidonghua, 2022
There are some problems in coal gangue detection, such as small differences of characteristics between samples and dense targets. This leads to low precision and poor real-time performance of the existing coal gangue detection methods.
GUI Fangjun, LI Yao
doaj   +1 more source

Improved GBS-YOLOv5 algorithm based on YOLOv5 applied to UAV intelligent traffic

Scientific Reports, 2023
Abstract As the road traffic situation becomes complex, the task of traffic management takes on an increasingly heavy load. The air-to-ground traffic administration network of drones has become an important tool to promote the high quality of traffic police work in many places.
Haiying Liu, Xuehu Duan, Haitong Lou, Jason Gu, Haonan Chen, Lingyun Bi   +5 more
openaire   +3 more sources

Automatic Real-Time Detection of Infant Drowning Using YOLOv5 and Faster R-CNN Models Based on Video Surveillance

Journal of Social Computing, 2023
Infant drowning has occurred frequently in swimming pools recent years, which motivates the research on automatic real-time detection of the accident. Unlike youths or adults, swimming infants are small in terms of size and motion range, and unable to ...
Qianen He, Zhiqiang Mei, Huisheng Zhang, Xiuying Xu   +3 more
doaj   +1 more source

HIC-YOLOv5: Improved YOLOv5 For Small Object Detection

2024 IEEE International Conference on Robotics and Automation (ICRA)
Small object detection has been a challenging problem in the field of object detection. There has been some works that proposes improvements for this task, such as adding several attention blocks or changing the whole structure of feature fusion networks.
Shiyi Tang, Yini Fang, Shu Zhang
openaire   +4 more sources

YOLOv5s-CA: A Modified YOLOv5s Network with Coordinate Attention for Underwater Target Detection

Sensors, 2023
Underwater target detection techniques have been extensively applied to underwater vehicles for marine surveillance, aquaculture, and rescue applications. However, due to complex underwater environments and insufficient training samples, the existing underwater target recognition algorithm accuracy is still unsatisfactory.
Ge Wen, Shaobao Li, Fucai Liu, Xiaoyuan Luo, Meng Joo Er, Mufti Mahmud, Tao Wu   +6 more
openaire   +3 more sources

DDVC-YOLOv5: An Improved YOLOv5 Model for Road Defect Detection

IEEE Access
Road defect detection is crucial for enhancing traffic safety, optimizing urban management efficiency, and promoting sustainable urban development. Traditional manual detection methods are inefficient and costly, and most deep learning-based road defect detection models lack superior feature extraction capabilities in complex environments.
Shihao Zhong, Chunlin Chen, Wensheng Luo, Siyuan Chen   +3 more
openaire   +2 more sources

Swin-YOLOv5: Research and Application of Fire and Smoke Detection Algorithm Based on YOLOv5

Computational Intelligence and Neuroscience, 2022
Accurate monitoring of fire and smoke plays an irreplaceable role in preventing fires and safeguarding the safety of citizens' lives and property. The network structure of YOLOv5 is simple, but using convolution to extract features will lead to some problems such as limited receptive field, poor feature extraction ability, and insufficient feature ...
Shangjie Ge Zhang, Fengxi Zhang, Yuyang Ding, Yu Li   +3 more
openaire   +2 more sources