Presentation 2007-03-16
Generation of Holographic Movies with Frame Interpolation using Coherent Neural Networks : Error-reduction using a Hybrid Learning Method
Chor Shen TAY, Ken TANIZAWA, Akira HIROSE,
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Abstract(in English) Computer Generated Holograms (CGH) are commonly used in optical tweezers which are employed in many different research fields. Frame interpolation using coherent neural networks (CNN) based on correlation learning can be used to generate holographic movies efficiently. However, the error that appears in the interpolated CGH images need to be reduced even further so that the method with frame interpolation can be accepted for use generally. In this paper, we propose a new hybrid CNN learning method that is able to generate the movies almost just, as efficiently and yet reduces even more error that is present in the generated holographic images as compared to the method based solely on correlation learning.
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Keyword(in English) Computer Generated Holograms (CGH) / Coherent Neural Networks (CNN) / optical tweezers / frame interpolation / error-reduction / hybrid learning method
Paper # NC2006-210
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Committee NC
Conference Date 2007/3/9(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Generation of Holographic Movies with Frame Interpolation using Coherent Neural Networks : Error-reduction using a Hybrid Learning Method
Sub Title (in English)
Keyword(1) Computer Generated Holograms (CGH)
Keyword(2) Coherent Neural Networks (CNN)
Keyword(3) optical tweezers
Keyword(4) frame interpolation
Keyword(5) error-reduction
Keyword(6) hybrid learning method
1st Author's Name Chor Shen TAY
1st Author's Affiliation Department of Electronic Engineering, The University of Tokyo()
2nd Author's Name Ken TANIZAWA
2nd Author's Affiliation Department of Electronic Engineering, The University of Tokyo
3rd Author's Name Akira HIROSE
3rd Author's Affiliation Department of Electronic Engineering, The University of Tokyo
Date 2007-03-16
Paper # NC2006-210
Volume (vol) vol.106
Number (no) 590
Page pp.pp.-
#Pages 6
Date of Issue