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20182023
most citedDesign of Task-Specific Optical Systems Using Broadband Diffractive Neural Networks

291 citations · 2.5k across the 25 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

physics.optics2023★ 60 cited

All-optical image denoising using a diffractive visual processor

Cagatay Isıl, Tianyi Gan, F. Onuralp Ardic +9

Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers,…

physics.optics2023★ 31 cited

Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network

Che-Yung Shen, Jingxi Li, Deniz Mengu +1

As a label-free imaging technique, quantitative phase imaging (QPI) provides optical path length information of transparent specimens for various applications in biology, materials…

physics.optics2023★ 31 cited

Pyramid diffractive optical networks for unidirectional image magnification and demagnification

Bijie Bai, Xilin Yang, Tianyi Gan +4

Diffractive deep neural networks (D2NNs) are composed of successive transmissive layers optimized using supervised deep learning to all-optically implement various computational ta…

physics.optics2023★ 68 cited

Plasmonic photoconductive terahertz focal-plane array with pixel super-resolution

Xurong Li, Deniz Mengu, Aydogan Ozcan +1

Imaging systems operating in the terahertz part of the electromagnetic spectrum are in great demand because of the distinct characteristics of terahertz waves in penetrating many o…

physics.optics2023★ 37 cited

Quantitative phase imaging (QPI) through random diffusers using a diffractive optical network

Yuhang Li, Yi Luo, Deniz Mengu +2

Quantitative phase imaging (QPI) is a label-free computational imaging technique used in various fields, including biology and medical research. Modern QPI systems typically rely o…