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Paper Abstract and Keywords
Presentation 2019-06-13 13:15
Autoencoders having surplus neurons in a hidden layer
Akihiro Suzuki, Hakaru Tamukoh (KYUTECH)
Abstract (in Japanese) (See Japanese page) 
(in English) Unknown data is not compatible with a supervised training. This study employ autoencoders (AEs) to detect unknwon data. The AEs has surplus neurons in a hidden layer and gets a space to represent unknown data. In the proposed AEs, the surplus neurons are trained not to be reacted for target data, while they are trained to be reacted against non-target data. By this training method, the surplus neurons become to react except target data. This paper reports validation results using grayscale clothing image dataset.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / Autoencoders / Unknown Object / / / / /  
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Conference Information
Committee IEICE-SIS IPSJ-AVM 3DMT  
Conference Date 2019-06-13 - 2019-06-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Fukue Culture Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Intelligent Multimedia Systems, Applied Enbedded Systems, Three-Dimensional Image Technology (3DIT), etc. 
Paper Information
Registration To IEICE-SIS 
Conference Code 2019-06-SIS-AVM-3DIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Autoencoders having surplus neurons in a hidden layer 
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Keyword(1) Deep Learning  
Keyword(2) Autoencoders  
Keyword(3) Unknown Object  
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1st Author's Name Akihiro Suzuki  
1st Author's Affiliation Kyushu Institute of Technology (KYUTECH)
2nd Author's Name Hakaru Tamukoh  
2nd Author's Affiliation Kyushu Institute of Technology (KYUTECH)
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Speaker Author-1 
Date Time 2019-06-13 13:15:00 
Presentation Time 20 minutes 
Registration for IEICE-SIS 
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Volume (vol) vol.43 
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