Application of evolutionary and swarm optimization in computer vision: a literature survey Nakane, Takumi, Bold, Naranchimeg, Sun, Haitian, Lu, Xuequan, Akashi, Takuya and Zhang, Chao 2020, Application of evolutionary and swarm optimization in computer vision: a literature survey, IPSJ Transactions on Computer Vision and Applications, vol. 12, no. 3, pp. 1-34, doi: 10.1186/s41074-020-00065-9. Attached Files Name Description MIMEType Size Downloads Title Application of evolutionary and swarm optimization in computer vision: a literature survey Author(s) Nakane, Takumi Bold, Naranchimeg Sun, Haitian Lu, Xuequan orcid.org/0000-0003-0959-408X Akashi, Takuya Zhang, Chao Journal name IPSJ Transactions on Computer Vision and Applications Volume number 12 Issue number 3 Start page 1 End page 34 Total pages 34 Publisher SpringerOpen Place of publication London, Eng. Publication date 2020 ISSN 1882-6695 1882-6695 Keyword(s) Evolutionary algorithms Swarm algorithms Computer vision Literature survey Summary 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. Language eng DOI 10.1186/s41074-020-00065-9 Indigenous content off HERDC Research category C1 Refereed article in a scholarly journal Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30141575 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Link to full-text (open access)     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Tue, 08 Sep 2020, 09:06:01 EST Wed, 09 Sep 2020, 05:00:13 EST Wed, 09 Sep 2020, 06:04:41 EST Tue, 15 Sep 2020, 15:33:34 EST Tue, 15 Sep 2020, 15:35:34 EST Tue, 15 Sep 2020, 15:36:18 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 31 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Tue, 08 Sep 2020, 09:06:01 EST

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