Leveraging autocatalytic reactions for chemical domain image classification-Reference-Cited by-同舟云学术

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Leveraging autocatalytic reactions for chemical domain image classification

Published:2021 Issue:15 Volume:12 Page:5464-5472
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Arcadia Christopher E.¹²³⁴^ORCID,Dombroski Amanda⁵²³⁴,Oakley Kady⁵²³⁴,Chen Shui Ling⁵²³⁴,Tann Hokchhay¹²³⁴,Rose Christopher¹²³⁴,Kim Eunsuk⁵²³⁴^ORCID,Reda Sherief¹²³⁴,Rubenstein Brenda M.⁵²³⁴,Rosenstein Jacob K.¹²³⁴^ORCID

Affiliation:

1. School of Engineering

2. Brown University

3. Providence

4. USA

5. Department of Chemistry

Abstract

Kinetic models of autocatalytic reactions have mathematical forms similar to activation functions used in artificial neural networks. Inspired by these similarities, we use a copper-catalyzed reaction to perform digital image recognition tasks.

Funder

National Science Foundation

Defense Advanced Research Projects Agency

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/SC/D0SC05860B

Reference52 articles.

1. Autocatalyses

2. The rhythm of yeast

3. A model for a bistable biochemical trigger of mitosis

4. Caspases: Enemies Within

5. Self-replication of DNA by its encoded proteins in liposome-based synthetic cells

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