Results 11 to 20 of about 14,166 (237)

HIC-YOLOv5: Improved YOLOv5 For Small Object Detection

2024 IEEE International Conference on Robotics and Automation (ICRA)
Small object detection has been a challenging problem in the field of object detection. There has been some works that proposes improvements for this task, such as adding several attention blocks or changing the whole structure of feature fusion networks.
Shiyi Tang, Yini Fang, Shu Zhang
openaire   +5 more sources

เครื่องจ่ายยาอัตโนมัติเเละตรวจสอบความถูกต้องด้วยโมเดล YOLOv5 [PDF]

Journal of Computer and Creative Technology
วารสารคอมพิวเตอร์และเทคโนโลยีสร้างสรรค์, 2, 2, 45 ...
พลวัต ช่อผูก, ธนกฤต นูพิมพ์, ปิ่นพงษ์ เรืองระวีนุกิจ, อนุชา ลือบางใหญ่   +3 more
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PO-YOLOv5: A defect detection model for solenoid connector based on YOLOv5

PLOS ONE
Solenoid connectors play important role in electronic stability system design, with the features of small size, low cost, fast response time and high reliability. The main production process challenge for solenoid connectors is the accurate detection of defects, which is closely related to safe driving.
Ming Chen, Yuqing Liu, Xing Wei, Zichen Zhang, Oleg Gaidai, Hengshou Sui, Bin Li   +6 more
openaire   +5 more sources

Confidence Thresholds: Towards an Automated Workflow for Unmarked Wildlife Population Modelling With Camera Trap Data. [PDF]

Ecol Evol
Our study explores the application of confidence level thresholds to automated wildlife detections from camera trap data to generate detection histories that could circumvent the need for costly manual review. Our approach employs a study‐specific deep learning ensemble, which is an under‐utilised approach in ecology. Our scripted workflow connects the
Anschau M, Denman S, Hocking G, Hamilton G.   +3 more
europepmc   +2 more sources

The Predator-Prey Encounter Detection (PrED) Model: Detecting Interactions Between Rotifers and Algae Using Computer Vision and Machine Learning. [PDF]

Ecol Evol
Using a simpler predator‐prey pairing of a semi‐sessile rotifer and motile algae, the Predator‐Prey Encounter Detection (PrED) model aims to streamline and semi‐automate video analysis of species interactions using computer‐vision and machine learning techniques. Based on Ultralytics YOLOv5 architecture with an implementation of SORT tracking, the PrED
DeMattei BC, Hampton SE.
europepmc   +2 more sources

Research on mine vehicle tracking and detection technology based on YOLOv5

Systems Science & Control Engineering, 2022
Vehicle tracking detection, recognition and counting is an important part of vehicle analysis. Designing such a model with excellent performance is difficult. The traditional target detection algorithm based on artificial features has poor generalization
Kaijie Zhang, Chao Wang, Xiaoyong Yu, Aihua Zheng, Mingyue Gao, Zhenggao Pan, Guolong Chen, Zhiqi Shen   +7 more
doaj   +1 more source

GRP-YOLOv5: An Improved Bearing Defect Detection Algorithm Based on YOLOv5

Sensors, 2023
Currently, most chemical transmission equipment relies on bearings to support rotating shafts and to transmit power. However, bearing defects can lead to a series of failures in the equipment, resulting in reduced production efficiency. To prevent such occurrences, this paper proposes an improved bearing defect detection algorithm based on YOLOv5 ...
Zhao, Yue, Chen, Bolun, Liu, Bushi, Yu, Cuiying, Wang, Ling, Wang, Shanshan   +5 more
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DETECTION AND RECOGNITION OF ROAD SIGNS USING YOLOv5 [PDF]

Proceedings on Engineering Sciences, 2023
In the field of deep learning, a convolutional neural network is a class of artificial neural networks that became dominant in various computer vision tasks, which is widely used to solve complex problems in various areas, including driver assistance ...
Haitam Ettazi , Najat Rafalia , Jaafar Abouchabaka   +2 more
doaj   +1 more source

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   +3 more sources

YOLOv5-plum network structure diagram.

, 2023
Real-time, rapid, accurate, and non-destructive batch testing of fruit growth state is crucial for improving economic benefits. However, for plums, environmental variability, multi-scale, occlusion, overlapping of leaves or fruits pose significant ...
Qianqian Wu (818952), Xinyun Liang (13171051), Ming Lu (122276), Yupeng Niu (16698707), Jiong Mu (16698710)   +4 more
core   +1 more source