Application of evolutionary and swarm optimization in computer vision: a literature survey

Takumi Nakane; Naranchimeg Bold; Haitian Sun; Xuequan Lu; Takuya Akashi; Chao Zhang

doi:10.1186/s41074-020-00065-9

Application of evolutionary and swarm optimization in computer vision: a literature survey

Takumi Nakane, Naranchimeg Bold, Haitian Sun, Xuequan Lu, Takuya Akashi, Chao Zhang^*

^*Corresponding author for this work

Intellectual Information Engineering

Research output: Contribution to journal › Review article › peer-review

34 Scopus citations

Abstract

Evolutionary algorithms (EAs) and swarm algorithms (SAs) have shown their usefulness in solving combinatorial and NP-hard optimization problems in various research fields. However, in the field of computer vision, related surveys have not been updated during the last decade. In this study, inspired by the recent development of deep neural networks in computer vision, which embed large-scale optimization problems, we first describe a literature survey conducted to compensate for the lack of relevant research in this area. Specifically, applications related to the genetic algorithm and differential evolution from EAs, as well as particle swarm optimization and ant colony optimization from SAs and their variants, are mainly considered in this survey.

Original language	English
Article number	3
Journal	IPSJ Transactions on Computer Vision and Applications
Volume	12
Issue number	1
DOIs	https://doi.org/10.1186/s41074-020-00065-9
State	Published - 2020/12/01

Keywords

Computer vision
Evolutionary algorithms
Literature survey
Swarm algorithms

ASJC Scopus subject areas

Computer Vision and Pattern Recognition

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10.1186/s41074-020-00065-9

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AU - Akashi, Takuya

AU - Zhang, Chao

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Application of evolutionary and swarm optimization in computer vision: a literature survey

Abstract

Keywords

ASJC Scopus subject areas

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