Results 51 to 60 of about 7,483 (192)

Helmet detection method based on improved YOLOv5

工程科学学报
To address the challenge of low detection accuracy in existing safety helmet detection algorithms, particularly in scenarios with small targets, dense environments, and complex surroundings like construction sites, tunnels, and coal mines, we introduce ...
Gongyu HOU, Qinhuang CHEN, Zhenhua YANG, Youwen ZHANG, Danyang ZHANG, Haoxiang LI   +5 more
doaj   +1 more source

Survey on AI‐Enabled Computer Vision Technologies and Applications for Space Robotic Missions

Journal of Field Robotics, EarlyView.
ABSTRACT This survey provides a comprehensive overview of recent advancements and challenges in Artificial Intelligence (AI)‐enabled computer vision (CV) techniques for space robotic missions, spanning critical phases such as Entry, Descent, and Landing (EDL), orbital operations, and planetary surface exploration.
Maciej Quoos, Steven Kay, Julia Wajoras, Robert Field, Evridiki V. Ntagiou, Fakher Mohammad, Yang Gao   +6 more
wiley   +1 more source

PQD recognition using two-dimensional time-frequency spectrograms and an improved YOLOv5

Zhejiang dianli
As the penetration rate of renewable energy sources increases in new-type power systems， so too does the complexity of the grid structure， leading to more diverse and complex power quality disturbance （PQD）. To accurately identify power quality， a method
LI Xin, LYU Ganyun, GONG Yu, BI Ruihua, YE Jiaxing, LIU Xiaohong, YU Xiangyi   +6 more
doaj   +1 more source

เครื่องจ่ายยาอัตโนมัติเเละตรวจสอบความถูกต้องด้วยโมเดล YOLOv5

Journal of Computer and Creative Technology
วารสารคอมพิวเตอร์และเทคโนโลยีสร้างสรรค์, 2, 2, 45 ...
openaire   +2 more sources

A UAV‐based deep learning pipeline for intertidal macrobenthos monitoring: Behavioral and age classification in Tachypleus tridentatus

Remote Sensing in Ecology and Conservation, EarlyView.
The endangered tri‐spine horseshoe crab (Tachypleus tridentatus), a “living fossil” crucial to coastal ecology and biomedical research, is experiencing severe population declines. Effective conservation requires efficient monitoring, which traditional methods cannot deliver at scale. We develop an integrated UAV deep learning framework tailored to this
Xiaohai Chen, Yuyuan Bao, Ziwei Ying, Mujiao Xie, Ting Li, Jixing Zou, Jun Shi, Xiaoyong Xie   +7 more
wiley   +1 more source

Intelligent monitoring method for conveyor belt misalignment based on deep learning

Gong-kuang zidonghua
Existing methods for monitoring conveyor belt misalignment face challenges in terms of practicality, robustness, and the difficulty of dataset creation.
ZUO Mingming, ZHANG Xi, YANG Zihao, SUN Qifei, ZHANG Mengchao, ZHANG Yuan, LI Hu   +6 more
doaj   +1 more source

Yolov5s-PSG: Improved Yolov5s-Based Helmet Recognition in Complex Scenes

IEEE Access
In the field of industrial safety, due to the existence of color, distance and other reasons in complex industrial environments caused by the helmet small target detection methods have the problem of misdetection and omission, and the Yolov5s model for real-time detection of helmets is not ideal.
Yi Li, Xiaolin Shi, Xiaolong Xu, Han Zhang, Fan Yang   +4 more
openaire   +2 more sources

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao, Bangzhang Ma, Dianhan Xi, Jiaqi Wang, Yijia Chen, Yongying Liu, Xinlei Shao, Mowen Zhang, Guocheng Zhang, Jundong Chen, Katsunori Mizuno   +10 more
wiley   +1 more source

YOLOv5 garbage classification method with GhostNet

Dianzi Jishu Yingyong
Garbage classification is an important part of building ecological civilization. To solve the problem that heavyweight models are difficult to deploy to mobile devices, an improved garbage image classification method based on YOLOv5 network is proposed ...
Li Yao, Hu Junguo, Le Yang
doaj   +1 more source

Evaluating machine learning models for multi‐species wildlife detection and identification on remote sensed nadir imagery in South African savanna

Wildlife Biology, EarlyView.
This research paper investigates the efficacy of leading machine learning (ML) models for detecting and identifying ungulate species in African savanna using nadir imagery from unmanned aerial vehicles (UAVs). Traditional aerial counting methods, while widely used, suffer from significant limitations in accuracy and precision, in part due to human ...
Paul Allin, Fadel Seydou, Radloff Frans, Andrew Davies, Alison Leslie   +4 more
wiley   +1 more source