NDLI: Convolutional neural network-based multi-label classification of PCB defects

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Convolutional neural network-based multi-label classification of PCB defects

Content Provider	IET Digital Library
Author	Zhang, Linlin Jin, Yongqing Yang, Xuesong Li, Xia Duan, Xiaodong Sun, Yuan Liu, Hong
Abstract	Due to the rapid development of printed circuit board (PCB) design technology, inspection of PCB surface defects has become an increasingly critical issue. The classification of PCB defects facilitates the root causes of detects’ identification. As PCB defects may be intensive, the actual PCB classification should not be considered as a binary or multi-category problem. This type of problem is called multi-label classification problem. Recently, as one of the deep learning frameworks, a convolutional neural network (CNN) has a major breakthrough in many areas of image processing, especially in the image classification. This study proposes a multi-task CNN model to handle the multi-label learning problem by defining each label learning as a binary classification task. In this study, the multi-label learning is transformed into multiple binary classification tasks by customising the loss function. Extensive experiments demonstrate that the proposed method achieves great performance on the dataset of defects.
Starting Page	1612
Ending Page	1616
Page Count	5
Volume Number	2018
e-ISSN	20513305
Issue Number	Issue 16, Nov (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/joe/2018/16
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8279
Journal	The Journal of Engineering
Publisher	The Institution of Engineering and Technology
Publisher Date	2018-08-16
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	Automatic Optical Inspection Computer Vision And Image Processing Technique Convolution Convolutional Neural Network-based Multilabel Classification Deep Learning Frameworks Electronic Engineering Computing Feature Extraction Feedforward Neural Network Image Classification Image Recognition Learning in AI Multicategory Problem Multilabel Learning Problem Multiple Binary Classification Task Multitask CNN Model Neural Computing Technique PCB Defects PCB Surface Defects Inspection Printed Circuit Printed Circuit Board Design Technology
Content Type	Text
Resource Type	Article

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