Art

J-GLOBAL ID：200902106986306000   Reference number：02A0877497

Gradient-based PIV Using Neural Networks.

ニューラルネットワークを用いた勾配準拠型PIV

Author (5)： KIMURA I (Osaka Electro-Communication Univ., JPN) ,  SUSAKI Y (Osaka Electro-Communication Univ., JPN) ,  KIYOHARA R (Osaka Electro-Communication Univ., JPN) ,  KAGA A (Osaka Univ., JPN) ,  KUROE Y (Kyoto Inst. Technol., JPN)
Material： Journal of Visualization  (J Vis)
Volume： 5  Issue： 4  Page： 363-370  Publication year： 2002 
JST Material Number： L3794A  ISSN： 1343-8875  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： *particle image velocimetry ,...

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JST classification (1)： Experimental,test,measuring techniques and their apparatuses of fluids  (BC01020K)

Reference (5)：

• GRANT, I. Particle Image Velocimetry : a review. Proc. Instn. Mech. Engrs. 1997, 55-76
• HORN, B. K. P. Determining Optical Flow. Artificial Intelligence. 1981, 17, 185-203
• IDO, T. High Resolution Measurement of Flow Based on High-Order Image Reconstruction. Proc. 3rd ASME/JSME Joint Fluids Engineering Conference. 1999
• KUROE, Y. A Learning Method for Vector Field Approximation by Neural Networks. Proc. of 1998 IEEE International Joint Conference on Neural Networks (IJCNN'98)(Anchorage). 1998, 2300-2305
• OKUNO, T. Image Measurement by means of Spatio-Temporal Derivative Method. Proc. The International Workshop on PIV-Fukui '95. 1995, 167-173

Terms in the title (3)： ニューラルネットワーク ,  勾配 ,  PIV