Optical neural network2024 Elsevier B.V.Optical neural networks have shown promising advantages over its electronic counterpart due to fast computational speed, high throughput, and low energy consumption. For the deep neural networks mimicked by the cascaded phase masks, the conventional training ...
之前提到的衍射神经网络的运算都是在实空间完成的运算,而这篇论文展示了将图像进行傅里叶变换后再经过神经网络处理的方法。这种方法能够完成更加复杂的计算机视觉的任务(例如分割),同时也被证实了相比以往,傅里叶衍射神经网络在一些任务上有着更高的正确率和稳定性。 这篇论文中,作者使用傅里叶衍射神经网络,实现了计...
Diffractive Deep Neural Network (D${}^2$NN) Get Started OpticalLayer.py includes two types of Layers. Diffraction is the free space propagtion layer and DiffLayer provides phase modulation. from torch import nn from OpticalLayers import DiffLayer, Diffraction Build your own model like you do ...
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。
Figure1shows the proposed real-time multi-task diffractive deep neural network (D2NN) architecture. Specifically, in this work, our multi-task D2NN deploy image classification DNN algorithms with two tasks, i.e., classifying MNIST10 dataset and classifying Fashion-MNIST10 dataset. In a single-...
The development of artificial intelligence is typically focused on computer algorithms and integrated circuits. Recently, all-optical diffractive deep neural networks have been created that are based on passive structures and can perform complicated func
All-optical diffractive deep neural networks, consisting of multiple layers of diffractive surfaces, have been reported to perform various functions at the speed of light and low power consumption6. More importantly, the diffractive network enables parallel information processing, significantly enhancing ...
In this Letter we propose the Fourier-space diffractive deep neural network (F−DNN2) for all-optical image processing that performs advanced computer vision tasks at the speed of light. The F−DNN2 is achieved by placing the extremely compact diffra
the network can statistically learn. We term this framework as Diffractive Deep Neural Network (D 2 NN) and demonstrate its learning capabilities through both simulations and experiments. A D 2 NN can be physically created by using several transmissive and/or reflective layers, where each point...