Presentation	2020-10-09 Prediction of dislocation generation points in multicrystalline silicon photoluminescence image by convolutional neural network Hiroaki Kudo, Tetsuya Matsumoto, Kentaro Kutsukake, Noritaka Usami,
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Abstract(in Japanese)	(See Japanese page)
Abstract(in English)
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)
Paper #	PRMU2020-27
Date of Issue	2020-10-02 (PRMU)

Conference Information
Committee	PRMU
Conference Date	2020/10/9(2days)
Place (in Japanese)	(See Japanese page)
Place (in English)	Virtual
Topics (in Japanese)	(See Japanese page)
Topics (in English)	Recognition and understating of human
Chair	Yoichi Sato(Univ. of Tokyo)
Vice Chair	Akisato Kimura(NTT) / Masakazu Iwamura(Osaka Pref. Univ.)
Secretary	Akisato Kimura(Mobility Technologies) / Masakazu Iwamura(Chubu Univ.)
Assistant	Takashi Shibata(NTT) / Masashi Nishiyama(Tottori Univ.)

Paper Information
Registration To	Technical Committee on Pattern Recognition and Media Understanding
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Prediction of dislocation generation points in multicrystalline silicon photoluminescence image by convolutional neural network
Sub Title (in English)
Keyword(1)
1st Author's Name	Hiroaki Kudo
1st Author's Affiliation	Nagoya University(Nagoya Univ.)
2nd Author's Name	Tetsuya Matsumoto
2nd Author's Affiliation	Nagoya University(Nagoya Univ.)
3rd Author's Name	Kentaro Kutsukake
3rd Author's Affiliation	RIKEN(RIKEN)
4th Author's Name	Noritaka Usami
4th Author's Affiliation	Nagoya University(Nagoya Univ.)
Date	2020-10-09
Paper #	PRMU2020-27
Volume (vol)	vol.120
Number (no)	PRMU-187
Page	pp.pp.50-55(PRMU),
#Pages	6
Date of Issue	2020-10-02 (PRMU)