Results 31 to 40 of about 7,242,720 (244)
International Journal of Optics, 2021 A photonic artificial intelligence chip is based on an optical neural network (ONN), low power consumption, low delay, and strong antiinterference ability.
Yichen Sun +7 more
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Optical frontend for a convolutional neural network
Applied Optics, 2019 The parallelism of optics and the miniaturization of optical components using nanophotonic structures, such as metasurfaces present a compelling alternative to electronic implementations of convolutional neural networks. The lack of a low-power optical nonlinearity, however, requires slow and energy-inefficient conversions between the electronic and ...
Shane Colburn +3 more
openaire +4 more sources
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
Spectral splitting and concentration of broadband light using neural networks
APL Photonics, 2021 Compact photonic elements that control both the diffraction and interference of light offer superior performance at ultra-compact dimensions. Unlike conventional optical structures, these diffractive optical elements can provide simultaneous control of ...
Alim Yolalmaz, Emre Yüce
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Correlating matched-filter model for analysis and optimisation of neural networks [PDF]
, 1989 A new formalism is described for modelling neural networks by means of which a clear physical understanding of the network behaviour can be gained.
Midwinter, J.E. +7 more
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Broadband Backhaul Communication for Stratospheric Platforms: The Stratospheric Optical Payload Experiment (STROPEX) [PDF]
, 2006 A high bitrate optical downlink was performed by the stratospheric optical payload experiment (STROPEX), a part of the EU CAPANINA project. The STROPEX objectives were to design and build the necessary hardware to demonstrate an optical backhaul downlink
Knapek, Markus +9 more
core +1 more source
Free-space optical spiking neural network
PLoS ONENeuromorphic engineering has emerged as a promising avenue for developing brain-inspired computational systems. However, conventional electronic AI-based processors often encounter challenges related to processing speed and thermal dissipation.
Reyhane Ahmadi +2 more
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Hybrid training of optical neural networks
Optica, 2022 Optical neural networks are emerging as a promising type of machine learning hardware capable of energy-efficient, parallel computation. Today’s optical neural networks are mainly developed to perform optical inference after in silico training on digital simulators.
James Spall, Xianxin Guo, A. I. Lvovsky
openaire +4 more sources
Photonics, 2022 The convolution neural network (CNN) is a classical neural network with advantages in image processing. The use of multiport optical interferometric linear structures in neural networks has recently attracted a great deal of attention. Here, we use three
Xiaofeng Xu +4 more
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A Novel Method to Realize Optical Correlation Recognition Based on Neural Network
IEEE Photonics Journal, 2018 A neural network model is constructed according to 4F optical correlator. New optical filter is obtained by training the neural network. For recognition of distortion targets, the correlation peaks from correlator applying new filter are averagely ...
Ping Xu +5 more
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