Results 21 to 30 of about 7,211,078 (250)
Advanced Photonics, 2023 Optical neural networks (ONNs), enabling low latency and high parallel data processing without electromagnetic interference, have become a viable player for fast and energy-efficient processing and calculation to meet the increasing demand for hash rate.
Mao-Liang Wei +20 more
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Medical imaging analysis with artificial neural networks [PDF]
, 2010 Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection ...
Jiang, J., Ren, Jinchang, Trundle, P.
core +4 more sources
Netcast: Low-Power Edge Computing With WDM-Defined Optical Neural Networks [PDF]
Journal of Lightwave Technology, 2022 This article analyzes the performance and energy efficiency of Netcast, a recently proposed optical neural-network architecture designed for edge computing. Netcast performs deep neural network inference by dividing the computational task into two steps,
R. Hamerly +6 more
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Survey on Activation Functions for Optical Neural Networks
ACM Computing Surveys, 2023 Integrated photonics arises as a fast and energy-efficient technology for the implementation of artificial neural networks (ANNs). Indeed, with the growing interest in ANNs, photonics shows great promise to overcome current limitations of electronic ...
Oceane Destras +3 more
semanticscholar +1 more source
Research progress in optical neural networks: theory, applications and developments
PhotoniX, 2021 With the advent of the era of big data, artificial intelligence has attracted continuous attention from all walks of life, and has been widely used in medical image analysis, molecular and material science, language recognition and other fields.
Jia Liu +6 more
semanticscholar +1 more source
Physics-aware Differentiable Discrete Codesign for Diffractive Optical Neural Networks [PDF]
2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2022 Diffractive optical neural networks (DONNs) have attracted lots of attention as they bring significant advantages in terms of power efficiency, parallelism, and computational speed compared with conventional deep neural networks (DNNs), which have ...
Yingjie Li +3 more
semanticscholar +1 more source
Adaptive Photochemical Nonlinearities for Optical Neural Networks
Advanced Intelligent Systems, 2023 Optical neural networks (ONNs) hold great potential for faster and more energy‐efficient information processing in coherent photonic circuits. To realize ONNs, linear combinations and nonlinear activation functions have to be implemented in an optical ...
Marlon Becker +5 more
doaj +1 more source
Nature Communications, 2022 Large-scale silicon-based integrated artificial neural networks lack of silicon-integrated optical neurons. Here, Yu et al, report a self-monitored all-optical neural network enabled by nonlinear germanium-silicon photodiodes, making the photonic neural ...
Yang Shi +7 more
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Microring-based programmable coherent optical neural networks
Conference on Lasers and Electro-Optics, 2023 We design, simulate, and train a coherent optical neural network fully based on microring resonators including the linear multiplication and the reconfigurable nonlinear activation components, which shows advantages in terms of device footprint and ...
Jiahui Wang +3 more
semanticscholar +1 more source
Feature Extraction From Images Using Integrated Photonic Convolutional Kernel
IEEE Photonics Journal, 2022 Optical neural networks are expected to solve the problems of computational efficiency and energy consumption in neural networks. Herein, we experimentally implemented a 2 × 2 photonic convolutional kernel (PCK) using four on-chip micro-ring ...
Yulong Huang +6 more
doaj +1 more source