Results 21 to 30 of about 220,848 (275)
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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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
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Machine learning approach for computing optical properties of a photonic crystal fiber [PDF]
, 2019 Photonic crystal fibers (PCFs) are the specialized optical waveguides that led to many interesting applications ranging from nonlinear optical signal processing to high-power fiber amplifiers.
Aamir Gulistan +30 more
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Free-Space Optical Neural Network Based on Optical Nonlinearity and Pooling Operations
IEEE Access, 2021 Despite various optical realizations of convolutional neural networks (CNNs), optical implementation of nonlinear activation functions and pooling operations are still challenging problems.
Hoda Sadeghzadeh +2 more
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Sensors, 2022 In the last years, materializations of neuromorphic circuits based on nanophotonic arrangements have been proposed, which contain complete optical circuits, laser, photodetectors, photonic crystals, optical fibers, flat waveguides and other passive ...
Konstantinos Demertzis +3 more
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Optical implementation of the Hopfield model [PDF]
, 1985 Optical implementation of content addressable associative memory based on the Hopfield model for neural networks and on the addition of nonlinear iterative feedback to a vector-matrix multiplier is described.
Farhat, Nabil H. +3 more
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Training large-scale optoelectronic neural networks with dual-neuron optical-artificial learning
Nature Communications, 2023 Optoelectronic neural networks (ONN) are a promising avenue in AI computing due to their potential for parallelization, power efficiency, and speed.
Xiaoyun Yuan +4 more
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Performance analysis of different DCNN models in remote sensing image object detection
EURASIP Journal on Image and Video Processing, 2022 In recent years, deep learning, especially deep convolutional neural networks (DCNN), has made great progress. Many researchers use different DCNN models to detect remote sensing targets. Different DCNN models have different advantages and disadvantages.
Huaijin Liu +3 more
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Event-driven adaptive optical neural network
Science Advances, 2023 We present an adaptive optical neural network based on a large-scale event-driven architecture. In addition to changing the synaptic weights (synaptic plasticity), the optical neural network’s structure can also be reconfigured enabling various functionalities (structural plasticity).
Brückerhoff-Plückelmann, Frank +11 more
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Quantum optical neural networks [PDF]
npj Quantum Information, 2019 AbstractPhysically motivated quantum algorithms for specific near-term quantum hardware will likely be the next frontier in quantum information science. Here, we show how many of the features of neural networks for machine learning can naturally be mapped into the quantum optical domain by introducing the quantum optical neural network (QONN).
Gregory R. Steinbrecher +3 more
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