Particle Swarm Optimization for Automatically Evolving Convolutional Neural Networks for Image Classification Lawrence, T, Zhang, L, Lim, Chee Peng and Phillips, EJ 2021, Particle Swarm Optimization for Automatically Evolving Convolutional Neural Networks for Image Classification, IEEE Access, vol. 9, pp. 14369-14386, doi: 10.1109/ACCESS.2021.3052489. Attached Files Name Description MIMEType Size Downloads Title Particle Swarm Optimization for Automatically Evolving Convolutional Neural Networks for Image Classification Author(s) Lawrence, T Zhang, L Lim, Chee Peng orcid.org/0000-0003-4191-9083 Phillips, EJ Journal name IEEE Access Volume number 9 Start page 14369 End page 14386 Total pages 18 Publisher IEEE Place of publication Piscataway, N.J. Publication date 2021-01-26 ISSN 2169-3536 2169-3536 Keyword(s) ALGORITHM ARCHITECTURES CNN Computer Science Computer Science, Information Systems Convolutional neural network encoding Engineering Engineering, Electrical & Electronic evolutionary computation image classification particle swarm optimization Science & Technology Technology Telecommunications Language eng DOI 10.1109/ACCESS.2021.3052489 Field of Research 08 Information and Computing Sciences 09 Engineering 10 Technology HERDC Research category C1 Refereed article in a scholarly journal Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30147879 Document type: Journal Article Collections: Institute for Intelligent Systems Research and Innovation (IISRI) Open Access Collection Related Links Link Description Link to full-text (open access)   Connect to published version Go to link with your DU access privileges   Connect to Elements publication management system Go to link with your DU access privileges     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 Fri, 05 Feb 2021, 08:26:06 EST Sat, 06 Feb 2021, 04:01:32 EST Mon, 08 Feb 2021, 07:07:23 EST Sat, 06 Mar 2021, 01:35:59 EST Tue, 28 Jun 2022, 08:33:21 EST Tue, 28 Jun 2022, 12:13:30 EST Tue, 28 Jun 2022, 12:23:00 EST Mon, 04 Jul 2022, 06:08:15 EST Tue, 19 Jul 2022, 11:08:45 EST Wed, 27 Jul 2022, 00:36:43 EST Filtered Full Citation counts:   Cited 7 times in TR Web of Science Cited 9 times in Scopus Search Google Scholar Access Statistics: 7 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Fri, 05 Feb 2021, 08:26:06 EST