Results 31 to 40 of about 4,232 (214)

YOLOv5s-GTB: light-weighted and improved YOLOv5s for bridge crack detection

CoRR, 2022
In response to the situation that the conventional bridge crack manual detection method has a large amount of human and material resources wasted, this study is aimed to propose a light-weighted, high-precision, deep learning-based bridge apparent crack recognition model that can be deployed in mobile devices' scenarios.
openaire   +2 more sources

YOLOv5-OCDS: An Improved Garbage Detection Model Based on YOLOv5

Electronics, 2023
As the global population grows and urbanization accelerates, the garbage that is generated continues to increase. This waste causes serious pollution to the ecological environment, affecting the stability of the global environmental balance. Garbage detection technology can quickly and accurately identify, classify, and locate many kinds of garbage to ...
Qiuhong Sun, Xiaotian Zhang, Yujia Li, Jingyang Wang   +3 more
openaire   +1 more source

Underground personnel detection and tracking based on improved YOLOv5s and DeepSORT

Meitan kexue jishu, 2023
The real-time monitoring and tracking system of mine moving targets is an essential part of the construction of smart mines. The appearance of downhole inspection robots can realize the real-time monitoring of operators, but the existence of uneven ...
Xiaoqiang SHAO, Xin LI, Tao YANG, Yongde YANG, Shibo LIU, Zewen YUAN   +5 more
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

Study on the Detection Method for Daylily Based on YOLOv5 under Complex Field Environments

Plants, 2023
Intelligent detection is vital for achieving the intelligent picking operation of daylily, but complex field environments pose challenges due to branch occlusion, overlapping plants, and uneven lighting.
Hongwen Yan, Songrui Cai, Qiangsheng Li, Feng Tian, Sitong Kan, Meimeng Wang   +5 more
doaj   +1 more source

Detection of Broken Hongshan Buckwheat Seeds Based on Improved YOLOv5s Model

Agronomy, 2023
Breeding technology is one of the necessary means for agricultural development, and the automatic identification of poor seeds has become a trend in modern breeding.
Xin Li, Wendong Niu, Yinxing Yan, Shixing Ma, Jianxun Huang, Yingmei Wang, Renjie Chang, Haiyan Song   +7 more
doaj   +1 more source

Coal block abnormal behavior identification based on improved YOLOv5s + DeepSORT

, 2022
Coal block detection methods mainly include traditional image detection methods and deep learning target detection methods. The traditional image detection method has low detection precision and poor real-time performance, and can not accurately ...
YAN Jianxing, WANG Lixin, ZHANG Xuhui, WAN Jicheng, ZHANG Chao, HU Chengjun, WANG Dong, WANG Li   +7 more
core   +1 more source

Two Novel Models for Traffic Sign Detection Based on YOLOv5s

, 2023
Object detection and image recognition are some of the most significant and challenging  branches in the field of computer vision. The prosperous development of unmanned driving technology has made the detection and recognition of traffic signs crucial ...
Zhanlin Ji (14016624), Jingyi Zhao (1565662), Wei Bai (224622), Li Zhao (147498), Haiyang Zhang (132530), IVAN GANCHEV (12350872)   +5 more
core   +2 more sources

Optimized Yolov5s-Im for real-time apple flower detection in drone-based pollination

Smart Agricultural Technology
As traditional pollinators face increasing threats from climate change, the development of robotic pollination technology has become imperative, with apple flower detection emerging as a critical component of the technology.
Shahram Hamza Manzoor, Zhao Zhang, Hongwen Li, Qu Zhang, Kuifan Chen, C. Igathinathane, Tianzhong Li, Wei Li, Muhammad Naveed Tahir, Nabil Mustafa, Mustafa Mhamed   +10 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   +2 more sources