Using a 3D printer, a research team at the UCLA Samueli School of Engineering has created an artificial neural network that can analyze large volumes of data and identify objects at the speed of light. Called a diffractive deep neural network (D2NN), the technology uses the light scattering ...
(2018)All-optical machine learning using diffractive deep neural networks,程序员大本营,技术文章内容聚合第一站。
Here we introduce an all-optical deep learning framework, where the neural network is physically formed by multiple layers of diffractive surfaces that work in collaboration to optically perform an arbitrary function that the network can statistically learn. We term this framework as Diffractive Deep...
We introduce an all-optical Diffractive Deep Neural Network (D2NN) architecture that can learn to implement various functions after deep learning-based design of passive diffractive layers that work collectively. We experimentally demonstrated the success of this framework by creating 3D-printed D2NNs...
All-optical machine learning using diffractive deep neural networks. Science 361, 1004–1008 (2018). Article ADS MathSciNet CAS PubMed Google Scholar Weng, J. et al. Meta-neural-network for real-time and passive deep-learning-based object recognition. Nat. Commun. 11, 6309 (2020). ...
SmartGlass (SG) is a python implementation of a diffractive optical neural network. Currently, it supports training an all-optical classifier (e.g. classify hand-written digits MNIST dataset). Besides, the framework can also be used to design optics based on a task like focusing and beam steer...
A diffractive deep neural network is an optical machine learning structure that is capable of combining deep learning with optical diffraction and light-matter interaction to design diffractive surfaces that collectively carry out optical computation at
Fig. 1: Schematic of polarization-multiplexed all-optical diffractive computing. aOptical layout of the polarization-encoded diffractive network, where four isotropic diffractive layers and one array of linear polarizers are jointly used to perform two distinct, complex-valued linear transformations between...
"An optical computing module that implements a diffractive neural network is first used to extract information and reduce data dimensionality in a highly parallel way," explained Dr. Wu. This process is highly efficient and allows information to be extracted from high-resolution light fields. ...
在这里,我们介绍了一种物理机制,通过演示全光学衍射深度神经网络(D2NN, diffractive deep neural network)架构来执行机器学习,该架构可以使用基于深度学习的设计的集成工作的被动衍射层实现各种功能。我们创建了3D打印的D2NN,它实现了手写数字和时尚产品图像的分类,以及太赫兹光谱成像镜头的功能。 我们的全光学深度学习...