@inproceedings{55c01c86a5a04611902479212da0c930,
title = "Single-pixel Compressive Imaging with Single Photon Counting",
abstract = "We experimentally demonstrate a compressive imaging system by utilizing single-pixel detection at a single-photon level and a deep neural network. As a benchmark test, MNIST handwritten digits could be reconstructed at -27 dB signal to noise ratio.",
keywords = "Artificial neural networks, Benchmark testing, Electro-optical waveguides, Image reconstruction, Imaging, Machine learning, Photonics, Quantum computing, Remote sensing, Signal to noise ratio",
author = "Lili Li and Matthew Thomas and Santosh Kumar and Huang, {Yu Ping}",
note = "Publisher Copyright: {\textcopyright} Optica Publishing Group 2024 {\textcopyright} 2024 The Author(s); 2024 Conference on Lasers and Electro-Optics, CLEO 2024 ; Conference date: 07-05-2024 Through 10-05-2024",
year = "2024",
doi = "10.1364/cleo_at.2024.ath1g.5",
language = "English",
series = "2024 Conference on Lasers and Electro-Optics, CLEO 2024",
booktitle = "2024 Conference on Lasers and Electro-Optics, CLEO 2024",
}