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J-GLOBAL ID：202002224525894984   Reference number：20A1202206

Evaluation of turned and milled surfaces roughness using convolutional neural network

畳込みニューラルネットワークを用いた旋削および粉砕表面粗さの評価【JST・京大機械翻訳】

Author (6)： Rifai Achmad P. (School of Integrated Design Engineering, Faculty of Science and Technology, Keio University, Yokohama, Japan) ,  Rifai Achmad P. (Department of Mechanical and Industrial Engineering, Faculty of Engineering, Gadjah Mada University, Yogyakarta, Indonesia) ,  Aoyama Hideki (School of Integrated Design Engineering, Faculty of Science and Technology, Keio University, Yokohama, Japan) ,  Tho Nguyen Huu (Ho Chi Minh City University of Food Industry, Ho Chi Minh City, Viet Nam) ,  Md Dawal Siti Zawiah (Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia) ,  Masruroh Nur Aini (Department of Mechanical and Industrial Engineering, Faculty of Engineering, Gadjah Mada University, Yogyakarta, Indonesia)
Material： Measurement
Volume： 161  Page： Null  Publication year： 2020 
JST Material Number： W0315B  ISSN： 0263-2241  Document type： Article
Article type： 原著論文  Country of issue： Netherlands (NLD)  Language： ENGLISH (EN)

Abstract/Point： Existing computer vision metho...

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Thesaurus term： *convolution ,  surface structure ,  segmentation ,  loss function ,  *network ,  *lathe turning ,  milling (machining) ,  feature extraction ,  profilemeter ,  digital image ,  computer vision ,  prediction model ,  surface morphology ,  cutting condition ,  *convolutional neuralnetwork ,  structure ,  model

Author keywords (5)： Surface roughness evaluation ,  Turned and milled surfaces ,  Machine vision ,  Convolutional neural network ,  Loss functions

JST classification (5)： Measuring methods and instruments of mass,density,specific gravity  (AD05030Z) ,  Facilities for crop cultivation  (FB03040V) ,  Industrial culture methods,apparatus  (FK02020T) ,  Circulatory system models  (EL02020V) ,  Noise in general  (ND04010J)

Terms in the title (5)： 畳込みニューラルネットワーク ,  旋削 ,  粉砕 ,  表面粗さ ,  評価