研究者詳細 - 髙林　正典

論文 - 髙林　正典

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Self-referential holography meets AI technologies 招待有り査読有り国際誌

Masanori Takabayashi

Technical Digest - 14th International Conference on Optics-photonics Design & Fabrication (ODF'24) 2024年07月

Numerical Analysis on Contributions of Individual Layers in Self-Referential Holographic Deep Neural Network 査読有り国際誌

Taichi Takatsu, Rio Tomioka, Masanori Takabayashi

Technical Digest - 14th International Conference on Optics-photonics Design & Fabrication (ODF'24) 2024年07月

Numerical Simulations on Image Recognition by Self-Referential Holographic Deep Neural Network with Electronic Output Layer 査読有り国際誌

Rio Tomioka, Taichi Takatsu, Masanori Takabayashi

Technical Digest - 14th International Conference on Optics-photonics Design & Fabrication (ODF'24) 2024年07月

自己参照型ホログラフィの原理を用いた光電子深層ニューラルネットワークハードウェア招待有り査読有り

高林正典，冨岡莉生

フォトニクスニュース ( 応用物理学会フォトニクス分科会 ) 9 ( 3 ) 147 - 151 2024年03月

Numerical Simulation on Wavefront Transformation using Self-referential Holographic Deep Neural Network 査読有り国際誌

Rio Tomioka, Taichi Takatsu, Masanori Takabayashi

Program and Abstracts - The 5th International Symposium on Neuromorphic AI Hardware 2024年03月

Efficient Training Method using Transmission Matrix for Optoelectronic Deep Neural Network 査読有り国際誌

Taichi Takatsu, Rio Tomioka, Masanori Takabayashi

Program and Abstracts - The 5th International Symposium on Neuromorphic AI Hardware 2024年03月

Deep learning-based design of additional patterns in self-referential holographic data storage 査読有り国際誌

Chijiwa K., Takabayashi M.

Optical Review 31 ( 1 ) 28 - 40 2024年02月

担当区分：最終著者,　責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

Self-referential holographic data storage (SR-HDS), which has been proposed as a novel implementation method for holographic data storage (HDS), enables holographic recording without a reference beam. In addition to the signal pattern (SP) to be recorded, an additional pattern (AP) that affects the reconstruction quality is used in SR-HDS. One of the methods for obtaining a designed AP that contributes to high-quality reconstruction involves utilizing local search algorithms, such as the hill climbing (HC) method. However, designing an AP using this method typically requires a significant amount of time. In this study, we proposed a new AP-designing method that uses a deep neural network. By training a network with pairs of SP and designed AP based on a local search algorithm, a designed AP that improves the reconstruction quality of an arbitrary SP can be instantly obtained. APs designed using the deep learning-based method improved the reconstruction quality of SPs to the same level as those designed using the method based on local search algorithm, whereas the time required to obtain one designed AP was reduced by three or four orders of magnitude.

DOI： 10.1007/s10043-023-00856-2

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85180227764&origin=inward

Optical neural network hardware using self-referential holography 招待有り査読有り国際誌

Masanori Takabayashi, Rio Tomioka

The 22nd international symposium on eco-materials processing and design (ISEPD 2024) 2024年01月

Self-referential holography and its application to data storage and optical neural network hardware 招待有り国際誌

Masanori Takabayashi

The 13th Japan-Korea Workshop on Digital Holography and Information Photonics Proceedings 2023年12月

Numerical simulation on phase-to-intensity conversion by self-referential holographic deep neural network 国際誌

Rio Tomioka, Masanori Takabayashi

The 13th Japan-Korea Workshop on Digital Holography and Information Photonics Proceedings 2023年12月

Deep neural network-based complex amplitude reconstruction from spatial-domain phase shifting digital holograms 国際誌

Shu Kajitani, Masanori Takabayashi

The 13th Japan-Korea Workshop on Digital Holography and Information Photonics Proceedings 2023年12月

Self-Referential Holography and Its Fusion with AI Technologies 招待有り査読有り国際誌

Masanori Takabayashi

International Symposium on Imaging, Sensing and Optical Memory (ISOM'23) Technical Digest 2023年11月

Additional pattern designing method with multi-plane evaluation of intensity distributions for self-referential holographic data storage 査読有り国際誌

Kazuki Chijiwa, Masanori Takabayashi

International Symposium on Imaging, Sensing and Optical Memory (ISOM'23) Technical Digest 2023年11月

Effectiveness and Concerns of Tissue Diagnosis Using Resolution-Enhanced Quantitative Phase Images by Deep Neural Network 査読有り国際誌

Sho Nezaki, Masanori Takabayashi

International Symposium on Imaging, Sensing and Optical Memory (ISOM'23) Technical Digest 2023年11月

Numerical simulations on optoelectronic deep neural network hardware based on self-referential holography 査読有り国際誌

Rio Tomioka, Masanori Takabayashi

Optical Review ( Springer ) 30 387 - 396 2023年04月

定量位相イメージングを用いた組織診断招待有り査読有り

高林正典

光学 ( 一般社団法人　日本光学会 ) 52 ( 3 ) 98 - 103 2023年03月

Optical Coherence Tomography Phase Study 査読有り国際誌

Shih-Hsiang Hsu,Masanori Takabayashi

Proceedings of The 9th international forum on Advanced Technologies (IFAT 2023) 2023年03月

Numerical Simulations of Optoelectronic AI Hardware using Transmission Matrix of Real Object 査読有り

Masanori Takabayashi, Rio Tomioka, Kaito Inoue, Atsushi Shibukawa

Program and proceedings The 4th International Symposium on Neuromorphic AI Hardware 2022年12月

Self-referential holographic neural network with single spatial light modulator 査読有り

Rio Tomioka, Masanori Takabayashi

Program and proceedings The 4th International Symposium on Neuromorphic AI Hardware 2022年12月

定量位相イメージングを用いた組織診断招待有り査読有り

高林正典

レーザー研究 ( 一般社団法人レーザー学会 ) 50 ( 11 ) 616 - 621 2022年11月

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