the Diffractive Deep Neural Network has been completed. The last part is training it, and I don't want to write down more details, which are intuitive, for convenience. Actually, Just using 2 layers, the
Here, we propose a diffractive deep neural network (D2NN) framework based on a three-layer all-dielectric phased transmitarray as hidden layers, which can perform the classification of handwritten digits. By tailoring the radius of a silicon nanodisk of a meta-atom, the metasurface can realize...
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...
onn_train.py add readme modify code May 23, 2023 readme.md add section result in readme May 23, 2023 Repository files navigation README Diffractive Deep Neural Network (D${}^2$NN) Get Started OpticalLayer.py includes two types of Layers. Diffraction is the free space propagtion layer an...
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
(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。
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 ...
To overcome this limitation, the ID2N2 can be used as a building block in larger scale optoelectronic deep neural network, where the nonlinear response of the detector module can act as a hidden nonlinear layer. Also, the output of the ID2N2 can be considered as an optically pre-processed...
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
8.The optical diffractive processing unit of claim 1, wherein the optical neural network comprises a three-layer optoelectronic diffractive deep neural network (D2NN). 9.The optical diffractive processing unit of claim 1, wherein the optical neural network comprises recurrent modules;an output of ...