コヒーレントニューラルネットワークに基づくフレーム内挿によるホログラフィック動画の生成 : ハイブリッド学習法による誤差の低減

概要

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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.
2007-03-09