Results 1 to 10 of about 557,137 (294)

RST-YOLOv8: An Improved Chip Surface Defect Detection Model Based on YOLOv8

Sensors
Surface defect detection in chips is crucial for ensuring product quality and reliability. This paper addresses the challenge of low identification accuracy in chip surface defect detection, which arises from the similarity of defect characteristics ...
Wenjie Tang, Yangjun Deng, Xu Luo
doaj   +1 more source

TGDNet: A Multi-Scale Feature Fusion Defect Detection Method for Transparent Industrial Headlight Glass

Sensors
In industrial production, defect detection for automotive headlight lenses is an essential yet challenging task. Transparent glass defect detection faces several difficulties, including a wide variety of defect shapes and sizes, as well as the challenge ...
Zefan Zhang, Jin Tang
doaj   +1 more source

Enhanced Infrared Defect Detection for UAVs Using Wavelet-Based Image Processing and Channel Attention-Integrated SSD Model

IEEE Access
In this paper, we develop a defect target detection algorithm based on image processing and feature matching to address background noise in the detection of defects in infrared images of Unmanned Aerial Vehicle (UAVs), as well as to improve real-time ...
Jining Zhao, RuiZhi Zhang, Shaogong Chen, Yanbo Duan, Zhiyuan Wang, Qingchen Li   +5 more
doaj   +1 more source

Editorial: software defect detection [PDF]

Automated Software Engineering, 2010
The most difficult aspect of producing software is getting it right. Defects plague all software projects and enormous expense and time go into ridding code of the worst of them. Consequently, the ASE Community has devoted much attention to the problem of software defect avoidance.
openaire   +1 more source

Improvement of mask R-CNN and deep learning for defect detection and segmentation in electronic products.

PLoS ONE
With the rapid development of industrial automation and intelligent manufacturing, defect detection of electronic products has become crucial in the production process. Traditional defect detection methods often face the problems of insufficient accuracy
Longjian Guo, Jianming Meng, Wei Hao, Deepak Kumar Jain   +3 more
doaj   +1 more source

TD-Net:tiny defect detection network for industrial products

Complex & Intelligent Systems
The detection of tiny defects in industrial products is important for improving the quality of industrial products and maintaining production safety. Currently, image-based defect detection methods are ineffective in detecting tiny and variously shaped ...
Rui Shao, Mingle Zhou, Min Li, Delong Han, Gang Li   +4 more
doaj   +1 more source

Optimising digital signal processor‐based defect detection in smart manufacturing with lightweight convolutional neural networks

IET Collaborative Intelligent Manufacturing
Industrial defect detection is an important part of intelligent manufacturing, and Internet of things (IoT)‐based defect detection is receiving more and more attention. Although deep learning (DL) can help defect detection reduce the cost and improve the
Han Yue, Rucen Wang, Yi Gao, Ailing Xia, Kaikai Su, Jianhua Zhang   +5 more
doaj   +1 more source

Unsupervised industrial image defect detection based on autoencoder and GANs. [PDF]

PLoS One
An S, Wu J, Li J.
europepmc   +1 more source

Lightweight Power Line Defect Detection Based on Improved YOLOv8n. [PDF]

Sensors (Basel)
Yin Y, Liu X, Wu K, Xu R, Zheng J, Mei F.   +5 more
europepmc   +1 more source

DETECTION OF FABRIC DEFECTS. [PDF]

International Journal of Advanced Research, 2016
Karanveer Singh, Jaspreet Kaleka
openaire   +1 more source