Results 121 to 130 of about 17,190 (230)

A lightweight personnel detection method for underground coal mines

Meitan kexue jishu
The underground environment of coal mines is complex and has more safety hazards. Personnel detection is an important part of ensuring safe production in coal mines and building smart mines. Commonly used detection algorithms have large parameter counts,
Shuai WANG, Wei YANG, Yuxiang LI, Jiaqi WU, Wei YANG   +4 more
doaj   +1 more source

YOLOV5 : Classify Kaggle WBC data set using transfer learning approach using LISC data set. [PDF]

White blood cells (WBCs), are essential constituents of the immune system, by providing organism\u27s defence against infections, inflammation, and various diseases.
Rohilla, Dr. Tilak Raj, Sharma, Vandita
core   +2 more sources

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

SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detection

, 2022
Domain adaptive object detection (DAOD) aims to alleviate transfer performance degradation caused by the cross-domain discrepancy. However, most existing DAOD methods are dominated by outdated and computationally intensive two-stage Faster R-CNN, which ...
Jiang, Fei, Lu, Hongtao, Zhou, Huayi
core  

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

Sign Language Recognition based on YOLOv5 Algorithm for the Telugu Sign Language

Sign language recognition (SLR) technology has enormous promise to improve communication and accessibility for the difficulty of hearing. This paper presents a novel approach for identifying gestures in TSL using the YOLOv5 object identification ...
B, Vishnu Vardhan Reddy., P, Vipul Reddy., Sukriti   +2 more
core