| Literature DB >> 31386516 |
Tao Yan1, Jiamin Wu1, Tiankuang Zhou1,2, Hao Xie1, Feng Xu3, Jingtao Fan1, Lu Fang2, Xing Lin1,4, Qionghai Dai1.
Abstract
In this Letter we propose the Fourier-space diffractive deep neural network (F-D^{2}NN) for all-optical image processing that performs advanced computer vision tasks at the speed of light. The F-D^{2}NN is achieved by placing the extremely compact diffractive modulation layers at the Fourier plane or both Fourier and imaging planes of an optical system, where the optical nonlinearity is introduced from ferroelectric thin films. We demonstrated that F-D^{2}NN can be trained with deep learning algorithms for all-optical saliency detection and high-accuracy object classification.Entities:
Year: 2019 PMID: 31386516 DOI: 10.1103/PhysRevLett.123.023901
Source DB: PubMed Journal: Phys Rev Lett ISSN: 0031-9007 Impact factor: 9.161