[HTML][HTML] Analog optical computing for artificial intelligence
The rapid development of artificial intelligence (AI) facilitates various applications from all
areas but also poses great challenges in its hardware implementation in terms of speed and …
areas but also poses great challenges in its hardware implementation in terms of speed and …
Microcomb-driven optical convolution for car plate recognition
The great success of artificial intelligence (AI) calls for higher-performance computing
accelerators, and optical neural networks (ONNs) with the advantages of high speed and …
accelerators, and optical neural networks (ONNs) with the advantages of high speed and …
Frequency-flow convolution empowered by high-speed thin-film lithium niobate modulators
H Zhou, B Wu, S Zhang, M Xu, X Cai… - … Conference (ACP) and …, 2024 - ieeexplore.ieee.org
Current optical convolution architectures face challenges like limited scalability, data
redundancy, and restricted processing bandwidth. We demonstrate an optical frequency …
redundancy, and restricted processing bandwidth. We demonstrate an optical frequency …
[HTML][HTML] 光学卷积计算的进展与挑战 (特邀)
周浩军， 周海龙， 董建绩 - Acta Optica Sinica, 2024 - opticsjournal.net
摘要卷积计算作为数学运算方法里的一项重要算子, 在信号处理和人工智能领域有着重要的意义
. 卷积神经网络(CNN) 作为深度学**领域最重要的网络之一, 在计算机视觉和自然语言处理等 …
. 卷积神经网络(CNN) 作为深度学**领域最重要的网络之一, 在计算机视觉和自然语言处理等 …
A modified supervised learning rule for training a photonic spiking neural network to recognize digital patterns
Y Zhang, S **ang, X Guo, A Wen, Y Hao - Science China Information …, 2021 - Springer
A modified supervised learning rule which is suitable for training photonic spiking neural
networks (SNN) is proposed for the first time. The proposed learning rule is independent of …
networks (SNN) is proposed for the first time. The proposed learning rule is independent of …