Evolutionary super-resolution

Baptiste Roziere; Nathanaël Carraz Rakotonirina; Vlad Hosu; Hanhe Lin; Andry Rasoanaivo; Olivier Teytaud; Camille Couprie

doi:10.1145/3377929.3389959

Evolutionary super-resolution

Baptiste Roziere, Nathanaël Carraz Rakotonirina, Vlad Hosu, Hanhe Lin, Andry Rasoanaivo, Olivier Teytaud, Camille Couprie

Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Super-resolution increases the resolution of an image. Using evolutionary optimization, we optimize the noise injection of a super-resolution method for improving the results. More generally, our approach can be used to optimize any method based on noise injection.

Original language	English
Title of host publication	GECCO '20
Subtitle of host publication	Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
Place of Publication	New York, NY
Publisher	Association for Computing Machinery
Pages	151-152
Number of pages	2
ISBN (Electronic)	9781450371278
DOIs	https://doi.org/10.1145/3377929.3389959
Publication status	Published - 8 Jul 2020
Event	2020 Genetic and Evolutionary Computation Conference, GECCO 2020 - Cancun, Mexico Duration: 8 Jul 2020 → 12 Jul 2020

Publication series

Name	GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

Conference

Conference	2020 Genetic and Evolutionary Computation Conference, GECCO 2020
Country/Territory	Mexico
City	Cancun
Period	8/07/20 → 12/07/20

ASJC Scopus subject areas

Computational Mathematics

Access to Document

10.1145/3377929.3389959

Cite this

Roziere, B., Rakotonirina, N. C., Hosu, V., Lin, H., Rasoanaivo, A., Teytaud, O., & Couprie, C. (2020). Evolutionary super-resolution. In GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (pp. 151-152). (GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion). Association for Computing Machinery. https://doi.org/10.1145/3377929.3389959

Roziere, Baptiste ; Rakotonirina, Nathanaël Carraz ; Hosu, Vlad et al. / Evolutionary super-resolution. GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. New York, NY : Association for Computing Machinery, 2020. pp. 151-152 (GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion).

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title = "Evolutionary super-resolution",

abstract = "Super-resolution increases the resolution of an image. Using evolutionary optimization, we optimize the noise injection of a super-resolution method for improving the results. More generally, our approach can be used to optimize any method based on noise injection.",

author = "Baptiste Roziere and Rakotonirina, {Nathana{\"e}l Carraz} and Vlad Hosu and Hanhe Lin and Andry Rasoanaivo and Olivier Teytaud and Camille Couprie",

note = "Funding Information: Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 251654672 – TRR 161 (Project A05). Publisher Copyright: {\textcopyright} 2020 Owner/Author.; 2020 Genetic and Evolutionary Computation Conference, GECCO 2020 ; Conference date: 08-07-2020 Through 12-07-2020",

year = "2020",

month = jul,

day = "8",

doi = "10.1145/3377929.3389959",

language = "English",

series = "GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion",

publisher = "Association for Computing Machinery",

pages = "151--152",

booktitle = "GECCO '20",

}

Roziere, B, Rakotonirina, NC, Hosu, V, Lin, H, Rasoanaivo, A, Teytaud, O & Couprie, C 2020, Evolutionary super-resolution. in GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, pp. 151-152, 2020 Genetic and Evolutionary Computation Conference, GECCO 2020, Cancun, Mexico, 8/07/20. https://doi.org/10.1145/3377929.3389959

Evolutionary super-resolution. / Roziere, Baptiste; Rakotonirina, Nathanaël Carraz; Hosu, Vlad et al.
GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. New York, NY: Association for Computing Machinery, 2020. p. 151-152 (GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Evolutionary super-resolution

AU - Roziere, Baptiste

AU - Rakotonirina, Nathanaël Carraz

AU - Hosu, Vlad

AU - Lin, Hanhe

AU - Rasoanaivo, Andry

AU - Teytaud, Olivier

AU - Couprie, Camille

PY - 2020/7/8

Y1 - 2020/7/8

N2 - Super-resolution increases the resolution of an image. Using evolutionary optimization, we optimize the noise injection of a super-resolution method for improving the results. More generally, our approach can be used to optimize any method based on noise injection.

AB - Super-resolution increases the resolution of an image. Using evolutionary optimization, we optimize the noise injection of a super-resolution method for improving the results. More generally, our approach can be used to optimize any method based on noise injection.

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U2 - 10.1145/3377929.3389959

DO - 10.1145/3377929.3389959

M3 - Conference contribution

AN - SCOPUS:85089746811

T3 - GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

SP - 151

EP - 152

BT - GECCO '20

PB - Association for Computing Machinery

CY - New York, NY

T2 - 2020 Genetic and Evolutionary Computation Conference, GECCO 2020

Y2 - 8 July 2020 through 12 July 2020

ER -

Roziere B, Rakotonirina NC, Hosu V, Lin H, Rasoanaivo A, Teytaud O et al. Evolutionary super-resolution. In GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. New York, NY: Association for Computing Machinery. 2020. p. 151-152. (GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion). doi: 10.1145/3377929.3389959

Evolutionary super-resolution

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