Paper ID: 2211.03576

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

Zihan Zang, Haoqiang Wang, Yunpeng Xu

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.

Submitted: Nov 4, 2022