Edge4Real: A cost-effective edge computing based human behaviour recognition system for human-centric software engineering Shao, Di, Liu, Xiao, Cheng, Ben, Wang, Owen and Hoang, Thuong Ngoc 2020, Edge4Real: A cost-effective edge computing based human behaviour recognition system for human-centric software engineering, in ASE2020 : Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering, Association for Computing Machinery (ACM), New York, N.Y., pp. 1287-1291, doi: 10.1145/3324884.3415297. Attached Files Name Description MIMEType Size Downloads Title Edge4Real: A cost-effective edge computing based human behaviour recognition system for human-centric software engineering Author(s) Shao, Di Liu, Xiao orcid.org/0000-0001-8400-5754 Cheng, Ben Wang, Owen Hoang, Thuong Ngoc orcid.org/0000-0001-7354-260X Conference name ASE2020. Automated Software Engineering. IEEE/ACM International Conference (35th : 2020 : Melbourne, Victoria - Virtual Event Australia) Conference location Melbourne, Victoria - Virtual Event Australia Conference dates 21 - 25 Sep. 2020 Title of proceedings ASE2020 : Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering Publication date 2020 Start page 1287 End page 1291 Total pages 5 Publisher Association for Computing Machinery (ACM) Place of publication New York, N.Y. Keyword(s) human behaviour recognition human centric software engineering edge computing virtual reality CORE2020 A ISBN 9781450367684 ISSN 1938-4300 2643-1572 Language eng DOI 10.1145/3324884.3415297 Indigenous content off HERDC Research category E1 Full written paper - refereed Copyright notice ©2020, Association for Computing Machinery Persistent URL http://hdl.handle.net/10536/DRO/DU:30147445 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version 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. Versions Version Filter Type Thu, 21 Jan 2021, 13:28:35 EST Fri, 22 Jan 2021, 04:02:13 EST Fri, 22 Jan 2021, 05:06:06 EST Fri, 22 Jan 2021, 08:23:02 EST Tue, 02 Feb 2021, 05:05:04 EST Tue, 30 Mar 2021, 17:12:36 EST Tue, 30 Mar 2021, 17:24:27 EST Tue, 30 Mar 2021, 18:34:39 EST Wed, 19 May 2021, 13:42:23 EST Sat, 12 Jun 2021, 02:32:21 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 67 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Thu, 21 Jan 2021, 13:28:35 EST

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.