Toward surface defect detection in electronics manufacturing by an accurate and lightweight YOLO-style object detector

J Wang, H Dai, T Chen, H Liu, X Zhang, Q Zhong… - Scientific Reports, 2023 - nature.com
In electronics manufacturing, surface defect detection is very important for product quality
control, and defective products can cause severe customer complaints. At the same time, in …

Detection and location of safety protective wear in power substation operation using wear-enhanced YOLOv3 algorithm

B Zhao, H Lan, Z Niu, H Zhu, T Qian, W Tang - IEEE Access, 2021 - ieeexplore.ieee.org
Wearing personal safety protective equipment (PSPE) plays a key role in reducing electrical
injuries to electrical workers. However, substation employees often ignore this regulation …

Insulator faults detection based on deep learning

MW Adou, H Xu, G Chen - 2019 IEEE 13th International …, 2019 - ieeexplore.ieee.org
Electrical insulators are mainly used in transmission system for electrical insulation and
mechanical support purpose. Since the insulators are exposed to environment, they can be …

PCB-YOLO: An improved detection algorithm of PCB surface defects based on YOLOv5

J Tang, S Liu, D Zhao, L Tang, W Zou, B Zheng - Sustainability, 2023 - mdpi.com
To address the problems of low network accuracy, slow speed, and a large number of model
parameters in printed circuit board (PCB) defect detection, an improved detection algorithm …

A novel yolov3 algorithm-based deep learning approach for waste segregation: Towards smart waste management

S Kumar, D Yadav, H Gupta, OP Verma, IA Ansari… - Electronics, 2020 - mdpi.com
The colossal increase in environmental pollution and degradation, resulting in ecological
imbalance, is an eye-catching concern in the contemporary era. Moreover, the proliferation …

An enhanced detection method of PCB defect based on improved YOLOv7

Y Yang, H Kang - Electronics, 2023 - mdpi.com
Printed circuit boards (PCBs) are a critical component of modern electronic equipment,
performing a crucial role in the electronic information industry chain. However, accurate …

Research on tiny target detection technology of fabric defects based on improved Yolo

X Yue, Q Wang, L He, Y Li, D Tang - Applied Sciences, 2022 - mdpi.com
Fabric quality plays a crucial role in modern textile industry processes. How to detect fabric
defects quickly and effectively has become the main research goal of researchers. The You …

Real-time railroad track components inspection based on the improved YOLOv4 framework

F Guo, Y Qian, Y Shi - Automation in construction, 2021 - Elsevier
Abstract According to the Federal Railroad Administration (FRA) database, track component
failure is one of the major factors causing train accidents. To improve railroad safety and …

[HTML][HTML] Litter detection with deep learning: A comparative study

M Córdova, A Pinto, CC Hellevik, SAA Alaliyat… - Sensors, 2022 - mdpi.com
Pollution in the form of litter in the natural environment is one of the great challenges of our
times. Automated litter detection can help assess waste occurrences in the environment …

[HTML][HTML] Identification method of typical defects in transmission lines based on YOLOv5 object detection algorithm

J Yuan, X Zheng, L Peng, K Qu, H Luo, L Wei, J Jin… - Energy Reports, 2023 - Elsevier
In order to realize the automatic identification of typical defects in transmission lines, a
typical defect identification method for transmission lines based on You Only Look Once …