Presentation Information
[17p-K306-4]Demonstration of handwritten digit classification using the magneto-optical diffractive neural network
〇Hotaka Sakaguchi1, Takuma Honma1, Satoshi Sumi2, Hiroyuki Awano2, Hirofumi Nonaka3, Fatima Zahra Chafi1, Takayuki Ishibashi1 (1.Nagaoka Univ. of Tech., 2.Toyota Tech. Inst., 3.Aichi Inst. of Tech.)
Keywords:
optical computing,magneto-optical effect,Neuromorphic computing
To solve the energy consumption problem of deep neural network, we have studied on the development of a magneto-optical diffractive deep neural network (MO-D2NN) that utilize the magneto-optical effect of magnetic material. In our previous work, we reported the fabrication of hidden layer of MO-D2NN using thermomagnetic recording techniques on Bi-substitued iron garnet film, which exhibits large magneto-optical effect. In this report, we present the experimental demonstration of handwritten digit classification using the MO-D2NN.
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