Results 31 to 40 of about 220,848 (275)
An optical neural chip for implementing complex-valued neural network
Nature Communications, 2021 Most demonstrations of optical neural networks for computing have been so far limited to real-valued frameworks. Here, the authors implement complex-valued operations in an optical neural chip that integrates input preparation, weight multiplication and ...
H. Zhang +17 more
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Optical neural networks: The 3D connection [PDF]
Photoniques, 2020 We motivate a canonical strategy for integrating photonic neural networks (NN) by leveraging 3D printing. Our belief is that a NN’s parallel and dense connectivity is not scalable without 3D integration. 3D additive fabrication complemented with photonic signal transduction can dramatically augment the current capabilities of 2D CMOS and integrated ...
Dinc, Niyazi Ulas +2 more
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Songbird organotypic culture as an in vitro model for interrogating sparse sequencing networks [PDF]
, 2017 Sparse sequences of neuronal activity are fundamental features of neural circuit computation; however, the underlying homeostatic mechanisms remain poorly understood. To approach these questions, we have developed a method for cellular-resolution imaging
Blute, Todd +7 more
core +1 more source
Parity-time Symmetric Optical Neural Networks
Conference on Lasers and Electro-Optics, 2022 An optical neural network architecture is proposed that utilizes parity-time symmetric couplers as its building blocks. Gain–loss contrasts across the array are adjusted as a means to train the network.
Deng, Haoqin, Khajavikhan, Mercedeh
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Optical character recognition with neural networks
Вестник КазНУ. Серия математика, механика, информатика, 2019 XXI century is the age of global automation and digitization. There is high demand for optical recognition software, including character recognition. There are different approaches in solution optical recognition problem.
Aidarbek Shalakhmetov, Sanzhar Aubakirov
doaj +1 more source
Partitionable High-Efficiency Multilayer Diffractive Optical Neural Network
Sensors, 2022 A partitionable adaptive multilayer diffractive optical neural network is constructed to address setup issues in multilayer diffractive optical neural network systems and the difficulty of flexibly changing the number of layers and input data size.
Yongji Long +5 more
doaj +1 more source
, 2004 Automatic classification of variability is now possible with tools like neural networks. Here, we present two neural networks for the identification of microlensing events -- the first discriminates against variable stars and the second against ...
Afonso +32 more
core +1 more source
Automated Classification of Stellar Spectra. II: Two-Dimensional Classification with Neural Networks and Principal Components Analysis [PDF]
, 1997 We investigate the application of neural networks to the automation of MK spectral classification. The data set for this project consists of a set of over 5000 optical (3800-5200 AA) spectra obtained from objective prism plates from the Michigan Spectral
Bailer-Jones, Coryn A. L. +2 more
core +3 more sources
Magneto-optical diffractive deep neural network
Optics Express, 2022 We propose a magneto-optical diffractive deep neural network (MO-D2NN). We simulated several MO-D2NNs, each of which consists of five hidden layers made of a magnetic material that contains 100 × 100 magnetic domains with a domain width of 1 µm and an interlayer distance of 0.7 mm.
Takumi Fujita +6 more
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All-optical Fourier neural network using partially coherent light
ChipOptical neural networks present distinct advantages over traditional electrical counterparts, such as accelerated data processing and reduced energy consumption.
Jianwei Qin +5 more
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