Application of deep-learning for classification of fracture surface's sem image

被引:0
作者
YAMAGIWA K. [1 ]
机构
[1] National Institute for Occupational Safety and Health, Umezono, Kiyose
关键词
Fractography; Image analysis; Image classification; Neural network;
D O I
10.2472/jsms.69.644
中图分类号
学科分类号
摘要
[No abstract available]
引用
收藏
页码:644 / 649
页数:5
相关论文
共 8 条
[1]  
Okatani T., Shinsou Gakusyu, Koudansha, (2015)
[2]  
Komai K., Minoshima K., Koyama M., Development of Diagnostic Expert System for Environmentally Induced Cracking and Importance Evaluation of Knowledge, Trans. JSME, Series A, 57, pp. 188-194, (1991)
[3]  
Adachi Y., Microstructure Recognition by Deep Learning, Tetsu-to-Hagane, 12, 12, pp. 62-69, (2016)
[4]  
Ariyama K., Tensorflow hajimemashita, NextPublishing
[5]  
Szededy Christian, Et al., Going Deeper with Convolutions, (2014)
[6]  
Bishop C.M., Pattern Recognition and Machine Learning, (2006)
[7]  
Selevaraju R. R., Et al., (2017)
[8]  
Koh Pang Wei, Liang Percy, Understanding Blackbox Predictions via Influence Functions, (2017)