Results 91 to 100 of about 7,483 (192)

YOLOv5-DTW: Gesture recognition based on YOLOv5 and dynamic time warping for digital media design

Journal of Applied Science and Engineering
Gesture is one of the most natural ways for humans to communicate. Gesture recognition technology allows users to directly interact with digital media content through simple gestures, without resorting to traditional devices such as mouse, keyboard or ...
Lu Zhao, Jing Yu
doaj   +1 more source

Research on multi-objective detection method for incomplete information in coal mine underground

Meitan kexue jishu
Underground target detection technology in coal mines is an indispensable component of constructing a smart mine, providing real-time monitoring and recognition capabilities.
Lin SUN, Sheng CHEN, Xulong YAO, Yanbo ZHANG, Zhigang TAO, Peng LIANG   +5 more
doaj   +1 more source

Fe-Yolov5: Feature Enhancement Network Based on Yolov5 for Small Object Detection

SSRN Electronic Journal, 2022
Min Wang, Wenzhong Yang, Liejun Wang, Danny Chen, Fuyuan Wei, HaiLaTi KeZiErBieKe, Yuanyuan Liao   +6 more
openaire   +1 more source

The recognition of dust emission from open-pit mining roads based on cascaded convolutional networks by deep learning

Meitan kexue jishu
The dust emitted from open-pit mines poses a constant menace to both the health of the workers and the environment. However, the traditional manual decision-making and scheduled watering methods are constrained by delayed dust control and excessive water
Yunzhuo ZHOU, Zijing XU, Lin BI
doaj   +1 more source

ECTR-YOLOv5:Pedestrian detection in dense scenes based on improved YOLOv5

Abstract Pedestrian detection technology has reached a relatively mature level in sparse environments. However, accurate pedestrian detection in packed scenes still presents challenges owing to factors such as occlusion, high crowd density, and scale changes.
yiheng wu, laichun li, taihui liu, wei meng, chenwei wu   +4 more
openaire   +1 more source

R‐YOLOv5s: Improved YOLOv5s for Object Detection in Low‐Light Environments

International Journal of Intelligent Systems
In response to the challenge of low detection accuracy exhibited by mainstream object detection models in low‐light environments, this paper proposes a novel detection model named R‐YOLOv5s. The model incorporates several key enhancements to address this issue.
Yimeng Xia, Yuanmei Wang, Hao Luo, Shengzhe Liu, Tao Li   +4 more
openaire   +1 more source

Detection and tracking of safety helmet wearing based on deep learning

Open Computer Science
Failure to wear a helmet correctly is a significant cause of injury or death in the construction industry and industrial production. Traditional supervision methods predominantly rely on manual oversight, incurring substantial costs and demonstrating ...
Liang Hua, Yang Liqin, Chen Jinhua, Liu Xin, Hang Guihua   +4 more
doaj   +1 more source

Forest fire detection and recognition method based on improved YOLOv5-ACE algorithm. [PDF]

PLoS One
Zhao Y, Tang C.
europepmc   +1 more source

Deep learning-based detection of retinal detachment with vitreous hemorrhage in ocular ultrasound images. [PDF]

Sci Rep
Toyama N, Hidaka T, Tamura H, Ikeda Y.
europepmc   +1 more source

Heat exchanger pipe orifice recognition using an improved YOLOv5 model integrated with dual attention mechanisms. [PDF]

Sci Rep
Yang R, Zhu Y, Xu B, Dai W, Ji S, Meng D.   +5 more
europepmc   +1 more source