WEKO3
アイテム
Self-Referential Holographic Data Storage with Integrated Denoising Function by Deep Learning
http://hdl.handle.net/10228/0002001763
http://hdl.handle.net/10228/0002001763d3103737-9459-4263-b04c-004e4dd0c111
| 名前 / ファイル | ライセンス | アクション |
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neuro_105.pdf (576.5 KB)
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| アイテムタイプ | 共通アイテムタイプ(1) | |||||||||||||||
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| 公開日 | 2025-07-10 | |||||||||||||||
| タイトル | ||||||||||||||||
| タイトル | Self-Referential Holographic Data Storage with Integrated Denoising Function by Deep Learning | |||||||||||||||
| 言語 | en | |||||||||||||||
| 著者 |
Eto, Yuta
× Eto, Yuta
× Tomioka, Rio
× Takatsu, Taichi
× 高林, 正典
WEKO
35482
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| 抄録 | ||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||
| 内容記述 | Self-referential holographic data storage (SR-HDS) which is one of the implementation methods of holographic data storage (HDS) enables holographic digital data recording with an one-beam optical geometry [1]．In HDS, including SR-HDS, it is desired that the datapages are reconstructed as clear as possible. For this purpose, a denoising method using deep learning for noisy reconstructed datapages where it is caused by inter-and/or intra- page interactions has recently been paid attention [2]． In recent years, there has been a growing interest in technologies for the efficient hardware implementation of deep neural networks using optics [3]. One of them is self-referential holographic deep neural network (SR-HDNN), a method for parallel computation of deep neural networks through the application of holography [4]. Since SR-HDNN is implemented using the same optical system as SR-HDS, it is expected to implement both HDS and deep learning functions within a single optical system. In this study, we propose to improve the quality of the reconstructed datapages of SR-HDS using the principle of SR-HDNN. Specifically, we propose the system which integrates SR-HDS and SR-HDNN and investigate its feasibility. For this purpose, we perform the numerical simulations on SR-HDS with integrated denoising function by SRHDNN. |
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| 言語 | en | |||||||||||||||
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| 内容記述タイプ | Other | |||||||||||||||
| 内容記述 | International Symposium on Imaging, Sensing, and Optical Memory 2024, ISOM’24, October 20-23, 2024, Arcrea HIMEJI, Himeji, Hyogo, Japan | |||||||||||||||
| 言語 | en | |||||||||||||||
| 書誌情報 |
en : International Symposium on Imaging, Sensing and Optical Memory (ISOM '24) Technical Digest p. Mo-D-01, 発行日 2024-10 |
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| 出版社 | ||||||||||||||||
| 出版者 | 日本光学会 | |||||||||||||||
| 言語 | ja | |||||||||||||||
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| 言語 | eng | |||||||||||||||
| 資源タイプ | ||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||||||||
| 資源タイプ | conference paper | |||||||||||||||
| 出版タイプ | ||||||||||||||||
| 出版タイプ | AM | |||||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||||||
| 会議記述 | ||||||||||||||||
| 会議名 | International Symposium on Imaging, Sensing, and Optical Memory 2024, ISOM’24 | |||||||||||||||
| 言語 | en | |||||||||||||||
| 開始年 | 2024 | |||||||||||||||
| 開始月 | 10 | |||||||||||||||
| 開始日 | 20 | |||||||||||||||
| 終了年 | 2024 | |||||||||||||||
| 終了月 | 10 | |||||||||||||||
| 終了日 | 23 | |||||||||||||||
| 開催会場 | Arcrea HIMEJI | |||||||||||||||
| 言語 | en | |||||||||||||||
| 開催地 | Hyogo | |||||||||||||||
| 言語 | en | |||||||||||||||
| 開催国 | JPN | |||||||||||||||
| 研究者情報 | ||||||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/100000508_ja.html | |||||||||||||||
| 連携ID | ||||||||||||||||
| 値 | 14643 | |||||||||||||||
