Knowledge Commons of Institute of Automation,CAS
SACNN: Spatial Adversarial Convolutional Neural Network for Textile Defect Detection | |
Hou, Wei1,2; Tao, Xian2; Ma, Wenzhi2; Xu, De1,2 | |
发表期刊 | FIBRES & TEXTILES IN EASTERN EUROPE |
ISSN | 1230-3666 |
2020-11-01 | |
卷号 | 28期号:6页码:127-133 |
摘要 | Constructing textile defect detection systems is significant for quality control in industrial production, but it is costly and laborious to label sufficient detailed samples. This paper proposes a model called 'spatial adversarial convolutional neural network' which tries to solve the problem above by only using the image-level label. It consists of two parts: a feature extractor and feature competition. Firstly, a string of convolutional blocks is used as a feature extractor. After feature extraction, a maximum greedy feature competition is taken amongfeatures in thefeature layer. The feature competition mechanism can lead the network to converge to the defect location. To evaluate this mechanism, experiments were carried on two datasets. As the training time increases, the model can spontaneously focus on the actual defective location, and is robust towards an unbalanced sample. The classification accuracy of the two datasets can reach more than 98%, and is comparable with the method of labelling samples in detail. Detection results show that defect location from the model is more compact and accurate than in the Grad-CAM method. Experiments show that our model has potential usage in defect detection in an industrial environment. |
关键词 | textile defect detection feature extraction feature competition CNN |
DOI | 10.5604/01.3001.0014.3808 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61703399] ; National Natural Science Foundation of China[62066004] |
项目资助者 | National Natural Science Foundation of China |
WOS研究方向 | Materials Science |
WOS类目 | Materials Science, Textiles |
WOS记录号 | WOS:000591209000018 |
出版者 | INST CHEMICAL FIBRES |
七大方向——子方向分类 | 人工智能+制造 |
国重实验室规划方向分类 | 先进智能应用与转化 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/42687 |
专题 | 中国科学院工业视觉智能装备工程实验室_精密感知与控制 |
通讯作者 | Hou, Wei |
作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 2.Chinese Acad Sci, Res Ctr Precis Sensing & Control, Inst Automat, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Hou, Wei,Tao, Xian,Ma, Wenzhi,et al. SACNN: Spatial Adversarial Convolutional Neural Network for Textile Defect Detection[J]. FIBRES & TEXTILES IN EASTERN EUROPE,2020,28(6):127-133. |
APA | Hou, Wei,Tao, Xian,Ma, Wenzhi,&Xu, De.(2020).SACNN: Spatial Adversarial Convolutional Neural Network for Textile Defect Detection.FIBRES & TEXTILES IN EASTERN EUROPE,28(6),127-133. |
MLA | Hou, Wei,et al."SACNN: Spatial Adversarial Convolutional Neural Network for Textile Defect Detection".FIBRES & TEXTILES IN EASTERN EUROPE 28.6(2020):127-133. |
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18_Hou_SACNN_2020_6.(3209KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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