Supervised dictionary learning supported classifier with feature fusion scheme to noninvasively detect TRISO-particle defects
文献类型：期刊论文
| 作者 | Guo, MS; Yang, X; Zhang, F; Zhong, YJ; Lin, J |
| 刊名 | JOURNAL OF NUCLEAR MATERIALS
 |
| 出版日期 | 2019 |
| 卷号 | 523页码:43-50 |
| 关键词 | COATED FUEL-PARTICLES COATING THICKNESS RECOGNITION |
| ISSN号 | 0022-3115 |
| DOI | 10.1016/j.jnucmat.2019.05.040 |
| 文献子类 | 期刊论文 |
| 英文摘要 | This paper presents a novel method to support analyzing TRISO-particle failure rate by exploiting X-ray phase contrast imaging (PCI) modality to nondestructively visualize inter-defects and supervised dictionary learning to automatically distinguish cracked particles. Histogram of oriented gradient (HOG) operator was combined with local binary pattern histogram Fourier (LBP-HF) descriptor by canonical correlation analysis (CCA) method in order to extract crack features more significantly. Label consistent K-singular value decomposition (LC K-SVD) dictionary learning followed to encode features with more discriminability and learn a dictionary capable of excluding noise and intra-class variability to enforce recognition, with comparatively high recognition accuracy. (C) 2019 Elsevier B.V. All rights reserved. |
| 语种 | 英语 |
| 源URL | [http://ir.sinap.ac.cn/handle/331007/32226]  |
| 专题 | 上海应用物理研究所_中科院上海应用物理研究所2011-2017年 |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Shanghai Inst Appl Phys, Shanghai 201800, Peoples R China; 3.Chinese Acad Sci, Ctr Excellence TMSR Energy Syst, Shanghai Inst Appl Phys, Shanghai 201800, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Guo, MS,Yang, X,Zhang, F,et al. Supervised dictionary learning supported classifier with feature fusion scheme to noninvasively detect TRISO-particle defects[J]. JOURNAL OF NUCLEAR MATERIALS,2019,523:43-50. |
| APA | Guo, MS,Yang, X,Zhang, F,Zhong, YJ,&Lin, J.(2019).Supervised dictionary learning supported classifier with feature fusion scheme to noninvasively detect TRISO-particle defects.JOURNAL OF NUCLEAR MATERIALS,523,43-50. |
| MLA | Guo, MS,et al."Supervised dictionary learning supported classifier with feature fusion scheme to noninvasively detect TRISO-particle defects".JOURNAL OF NUCLEAR MATERIALS 523(2019):43-50. |
入库方式： OAI收割
来源：上海应用物理研究所
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