Results 11 to 20 of about 4,232 (214)

YOLOv5s-DSD: An Improved Aerial Image Detection Algorithm Based on YOLOv5s

Sensors, 2023
Due to the challenges of small detection targets, dense target distribution, and complex backgrounds in aerial images, existing object detection algorithms perform poorly in aerial image detection tasks. To address these issues, this paper proposes an improved algorithm called YOLOv5s-DSD based on YOLOv5s.
Chaoyue Sun, Yajun Chen, Ci Xiao, Longxiang You, Rongzhen Li   +4 more
openaire   +4 more sources

A lightweight ship target detection model based on improved YOLOv5s algorithm.

PLoS ONE, 2023
Real-time and accurate detection of ships plays a vital role in ensuring navigation safety and ship supervision. Aiming at the problems of large parameters, large computation quantity, poor real-time performance, and high requirements for memory and ...
Yuanzhou Zheng, Yuanfeng Zhang, Long Qian, Xinzhu Zhang, Shitong Diao, Xinyu Liu, Jingxin Cao, Haichao Huang   +7 more
doaj   +4 more sources

YOLOv5s-CA: A Modified YOLOv5s Network with Coordinate Attention for Underwater Target Detection

Sensors, 2023
Underwater target detection techniques have been extensively applied to underwater vehicles for marine surveillance, aquaculture, and rescue applications. However, due to complex underwater environments and insufficient training samples, the existing underwater target recognition algorithm accuracy is still unsatisfactory.
Ge Wen, Shaobao Li, Fucai Liu, Xiaoyuan Luo, Meng Joo Er, Mufti Mahmud, Tao Wu   +6 more
openaire   +4 more sources

Hydroponic Chinese flowering cabbage detection and localization algorithm based on improved YOLOv5s.

PLoS ONE
To achieve automated harvesting of hydroponic Chinese flowering cabbage, the detection and localization of the cabbage are crucial. This study proposes a two stages detection and localization algorithm for hydroponic Chinese flowering cabbage, which ...
Zhongjian Xie, Yaya Zhang, Weilin Wu, Yao Xiao, Xinwei Chen, Weiqi Chen, ZhuXuan Wan, Chunhua Lin   +7 more
doaj   +2 more sources

FES-YOLOv5s: A Lightweight Model for Agaricus Bisporus Detection

IEEE Access
Agaricus bisporus grows in complex environments and suffers from adhesion and occlusion problems. In this study, we propose a lightweight recognition model for Agaricus bisporus— FES-YOLOv5s—based on YOLOv5s.
Hao Ma, Haigang Ma, Jiangtao Ji, Hongwei Cui   +3 more
doaj   +2 more sources

Research on coal gangue detection in coal preparation plant based on YOLOv5s-FSW model

Gong-kuang zidonghua
A coal gangue detection method in coal preparation plant based on YOLOv5s-FSW model is proposed to address the problems of insufficient feature extraction, large parameter quantity, low detection precision, and poor real-time performance in existing coal
YAN Bijuan, WANG Kaimin, GUO Pengcheng, ZHENG Xinxu, DONG Hao, LIU Yong   +5 more
doaj   +2 more sources

Multi object detection of underground unmanned electric locomotives in coal mines based on SD-YOLOv5s-4L

Gong-kuang zidonghua, 2023
Due to complex environmental factors such as uneven illumination and high noise, unmanned electric locomotives in coal mines have low accuracy in multi object detection and difficulty in recognizing small objects.
ZHAO Wei, WANG Shuang, ZHAO Dongyang
doaj   +1 more source

Light-YOLOv5: A Lightweight Algorithm for Improved YOLOv5 in Complex Fire Scenarios

Applied Sciences, 2022
Fire-detection technology is of great importance for successful fire-prevention measures. Image-based fire detection is one effective method. At present, object-detection algorithms are deficient in performing detection speed and accuracy tasks when they are applied in complex fire scenarios. In this study, a lightweight fire-detection algorithm, Light-
Hao Xu, Bo Li, Fei Zhong
openaire   +3 more sources

Research on multi object detection in mining face based on FBEC-YOLOv5s

Gong-kuang zidonghua, 2023
A multi object detection algorithm based on FBEC-YOLOv5s is proposed to address the issues of reduced detection precision caused by large object scale spans, severe obstruction between multiple objects, and harsh environments in mining faces.
ZHANG Hui, SU Guoyong, ZHAO Dongyang
doaj   +1 more source

A Fast and Real-Time Machine Vision Evaluation System for Size Grading of <i>Agaricus bisporus</i> Based on Video. [PDF]

Food Sci Nutr
In this study, to address the problem of high cost and strong subjectivity of artificial grading of Agaricus bisporus, we propose a fast real‐time video‐based machine vision grading system, which achieves high‐speed grading of 1066.67 mushrooms per minute with an accuracy of 97.87% by lightweighting the YOLOv5 model and optimizing the balance between ...
Shui Q, Miao F, Liu S, Cao L, Jiang H, Lu J.   +5 more
europepmc   +2 more sources