招待論文

1. 髙林 正典, 冨岡 莉生, “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,” フォトニクスニュース 9, No. 3, pp. 147-151 (2024年3月). 

International Conference：国際会議・研究会

1. Rio Tomioka, Taichi Takatsu, and Masanori Takabayashi, "Numerical simulations on image recognition by self-referential holographic deep neural network with electronic output layer", 14th International Conference on Optics-Photonics Design and Fabrication (2024)．[poster, accepted] 
2. Taichi Takatsu, Rio Tomioka, and Masanori Takabayashi, "Numerical analysis on contributions of individual layers in self-referential holographic deep neural network", 14th International Conference on Optics-Photonics Design and Fabrication (2024). [poster, accepted]
3. Rio Tomioka, Taichi Takatsu, and Masanori Takabayashi, "Numerical simulation on wavefront transformation using self-referential holographic deep neural network", Program and proceedings the 5th International Symposium on Neuromorphic AI Hardware, O3-04/P1-22, p. 14 (Mar. 2024)
4. Taichi Takatsu, Rio Tomioka, and Masanori Takabayashi, "Efficient training method using transmission matrix for optoelectronic deep neural network", Program and proceedings the 5th International Symposium on Neuromorphic AI Hardware, P1-12, p. 25  (Mar. 2024) [poster]
5. Rio Tomioka and Masanori Takabayashi, “Numerical simulation on phase-to-intensity conversion by self-referential holographic deep neural network,” The 13th Japan-Korea Workshop on Digital Holography and Information Photonics (DHIP2023) proceeding, p. 54 (Dec. 2023). [poster, not-reviewed].
6. Rio Tomioka and Masanori Takabayashi, "Self-referential holographic deep neural network with single spatial light modulator," Program and proceedings the 4th International Symposium on Neuromorphic AI Hardware, P2-2, p. 35 (Dec. 2022). [poster]
7. Masanori Takabayashi, Rio Tomioka, Kaito Inoue, and Atsushi Shibukawa, "Numerical Simulations of Optoelectronic AI Hardware using Transmission Matrix of Real Object," Program and proceedings the 4th International Symposium on Neuromorphic AI Hardware, S-4, p. 7(Dec. 2022).
8. Rio Tomioka and Masanori Takabayashi, "Dependence of activation function on image recognition accuracy in self-referential holographic deep neural network," International Symposium on Imaging, Sensing, and Optical Memory (ISOM’22) Technical Digest, No. ITuPJ-01, 2pages (Jul. 2022).
9. Rio Tomioka and Masanori Takabayashi, "Self-referential holographic neural network with electronically implemented nonlinear layer," the 3rd International Symposium on Neuromorphic AI Hardware abstracts, P-AM8, p. 17 (Dec. 2022). [poster]
10. Masanori Takabayashi, Sae Isayama, and Rio Tomioka, "Hyperparameter tuning for accurate image classification using self-referential holographic neural network," International Workshop on Holography and Related Technologies (IWH 2021) Technical Digest, 11-P08 (Mar. 2022).
11. Rio Tomioka and Masanori Takabayashi, "Numerical simulations of neural network hardware based on self-referential holography," International Symposium on Imaging, Sensing, and Optical Memory (ISOM’21) Technical Digest， We-A-02， pp.123-124 (Oct. 2021).