DAD vision: opto-electronic co-designed computer vision with division adjoint method

11/04/2022
by   Zihan Zang, et al.
0

The miniaturization and mobility of computer vision systems are limited by the heavy computational burden and the size of optical lenses. Here, we propose to use a ultra-thin diffractive optical element to implement passive optical convolution. A division adjoint opto-electronic co-design method is also proposed. In our simulation experiments, the first few convolutional layers of the neural network can be replaced by optical convolution in a classification task on the CIFAR-10 dataset with no power consumption, while similar performance can be obtained.

READ FULL TEXT

page 2

page 5

research
09/19/2018

Light Field Neural Network

We introduce an optical neural network system made by off-the-shelf comp...
research
07/23/2018

PCNNA: A Photonic Convolutional Neural Network Accelerator

Convolutional Neural Networks (CNN) have been the centerpiece of many ap...
research
08/07/2023

Spatially Varying Nanophotonic Neural Networks

The explosive growth of computation and energy cost of artificial intell...
research
07/27/2017

Modular AWG-based Optical Shuffle Network

This paper proposes an arrayed-waveguide grating (AWG) based wavelength-...
research
12/20/2022

Sophisticated deep learning with on-chip optical diffractive tensor processing

The ever-growing deep learning technologies are making revolutionary cha...
research
08/26/2019

Oprema – The Relay Computer of Carl Zeiss Jena

The Oprema (Optikrechenmaschine = computer for optical calculations) was...
research
12/19/2020

Quantum Optical Convolutional Neural Network: A Novel Image Recognition Framework for Quantum Computing

Large machine learning models based on Convolutional Neural Networks (CN...

Please sign up or login with your details

Forgot password? Click here to reset