Results 91 to 100 of about 4,232 (214)

Multi-Scale Forest Fire Recognition Model Based on Improved YOLOv5s

, 2023
The frequent occurrence of forest fires causes irreparable damage to the environment and the economy. Therefore, the accurate detection of forest fires is particularly important. Due to the various shapes and textures of flames and the large variation in
Renjie Xu, Yucheng Gao, Haifeng Lin, Gong Chen, Hang Zhou, Zhongyuan Li, Di Bai   +6 more
core   +1 more source

Lightweight SCD-YOLOv5s: The Detection of Small Defects on Passion Fruit with Improved YOLOv5s

Accurate detection of surface defects on passion fruits is crucial for maintaining market competitiveness. Numerous small defects present significant challenges for manual inspection.
Zhenye Li, Sheng Xue, Min Wu, Tingting Zhu, Yu Zhou, Chao Ni   +5 more
core   +1 more source

YOLOv5s pruning method for edge computing of coal mine safety monitoring

Gong-kuang zidonghua
At present, the combination of edge computing and machine vision has a good application prospect for coal mine safety monitoring. But the storage space and computing resources at the edge are limited, and high-precision complex visual models are ...
CHEN Zhiwen, CHEN Ailiangfei, TANG Xiaodan, KE Haobin, JIANG Zhaohui, XIAO Fei   +5 more
doaj   +1 more source

Object Detection and Recognition Algorithm Based on YOLOv5 and the Fusion of Attention and Multistage Features [PDF]

Zhengzhou Daxue xuebao. Gongxue ban
To tackle the problem of low accuracy of detection and recognition for object in complex scenes, YOLOv5 object detection and recognition algorithm based on attention and multistage feature fusion(AMFF) was proposed in this study.
WANG Yu, BI Yu, SHI Jiantong, XIAO Hongbing, SUN Mei   +4 more
doaj   +1 more source

Underwater garbage detection method using lightweight YOLOv5s

Xi'an Gongcheng Daxue xuebao
Aimed at the problems of low recognition accuracy and low speed of small target detection algorithm, an improved lightweight YOLOv5s marine underwater garbage detection method, namely YOLOV5s-MCS, was proposed.Although the backbone network of YOLOv5s ...
WANG Yannian, LI Ying, LIAN Jihong
doaj   +1 more source

Research on Safety Helmet Detection Algorithm Based on Improved YOLOv5s

, 2023
Safety helmets are essential in various indoor and outdoor workplaces, such as metallurgical high-temperature operations and high-rise building construction, to avoid injuries and ensure safety in production.
Jun Yu, Tingting Liu, Yingjian Xu, Feihong Xu, Miao Tang, Qing An   +5 more
core   +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

CBG-YOLOv5s model performance.

The automatic detection of the degree of surface corrosion on metal structures is of significant importance for assessing structural damage and safety.
Zhitong Jia (17709113), Lingzhi Wu (133076), Zhendong Cui (18340284), Mingjiao Fu (18340281)   +3 more
core   +1 more source

YOLOv5s model structure framework.

The automatic detection of the degree of surface corrosion on metal structures is of significant importance for assessing structural damage and safety.
Zhitong Jia (17709113), Lingzhi Wu (133076), Zhendong Cui (18340284), Mingjiao Fu (18340281)   +3 more
core   +1 more source

YOLOv5s model performance.

The automatic detection of the degree of surface corrosion on metal structures is of significant importance for assessing structural damage and safety.
Zhitong Jia (17709113), Lingzhi Wu (133076), Zhendong Cui (18340284), Mingjiao Fu (18340281)   +3 more
core   +1 more source