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框...
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 ...
[光计算与人工智能]论文阅读2:All-optical machine learning using diffractive deep neural networks 努力加油的维克 光计算,计算摄影学36 人赞同了该文章 从这篇开始是衍射神经网络的相关笔记。 论文原地址如下,来自Science正刊。 https://www.science.org/doi/10.1126/science.aat8084www.science.org/doi/...
According to news reporting or iginating in Shanghai, People's Republicof China, by NewsRx journalists, resear ch stated, "All-optical diffractive deep neural networks (D(2)NNs)show a wide r ange of applications in image recognition and artificial vision due to their adv antages ofhigh-...
(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。
系统标签: diffractive deep optical neural learning networks Seediscussions,stats,andauthorprofilesforthispublicationat:https://.researchgate.net/publication/324745055All-OpticalMachineLearningUsingDiffractiveDeepNeuralNetworksArticle in Science·April2018DOI:10.1126/science.aat8084CITATIONS60READS7596authors,including...
Complex field imaging, which captures both the amplitude and phase information of input optical fields or objects, can offer rich structural insights into samples, such as their absorption and refractive index distributions. However, conventional image s
The forward model of a diffractive optical network can be mathematically formulated as a complex-valued matrix operator that multiplies an input field vector to create an output field vector at the detector plane/aperture. This operator is designed/trained using, e.g., deep learning to transform ...
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 the speed of light....
free-space optical layers. Here, we introduce a polarization-multiplexed diffractive processor to all-optically perform multiple, arbitrarily-selected linear transformations through a single diffractive network trained using deep learning. In this framework, an array of pre-selected linear polarizers is pos...