A deep learning-based model for tactile understanding on haptic data percutaneous needle treatment Khatami, Amin, Tai, Yonghang, Khosravi, Abbas, Wei, Lei, Moradi Dalvand, Mohsen, Zou, Min and Nahavandi, Saeid 2017, A deep learning-based model for tactile understanding on haptic data percutaneous needle treatment, in ICONIP 2017 : Proceedings of the 24th International Conference on Neural Information Processing, Springer International Publishing, Cham, Switerland, pp. 317-325, doi: 10.1007/978-3-319-70093-9_33. Attached Files Name Description MIMEType Size Downloads Title A deep learning-based model for tactile understanding on haptic data percutaneous needle treatment Author(s) Khatami, Amin Tai, Yonghang Khosravi, Abbas orcid.org/0000-0001-6927-0744 Wei, Lei orcid.org/0000-0001-8267-0283 Moradi Dalvand, Mohsen Zou, Min Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name Neural Information Processing. Conference (24th : 2017 : Guangzhou, China) Conference location Guangzhou, China Conference dates 2017/11/14 - 2017/11/18 Title of proceedings ICONIP 2017 : Proceedings of the 24th International Conference on Neural Information Processing Editor(s) Liu, Derong Xie, Shengli Li, Yuanqing Zhao, Dongbin El-Alfy, El-Sayed M Publication date 2017 Series Neural Information Processing Conference Start page 317 End page 325 Total pages 9 Publisher Springer International Publishing Place of publication Cham, Switerland Keyword(s) Tactile understanding Sequence classification Residual networks Time series ISBN 9783319700922 ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-319-70093-9_33 Indigenous content off HERDC Research category E1.1 Full written paper - refereed Persistent URL http://hdl.handle.net/10536/DRO/DU:30124014 Document type: Conference Paper Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research 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 Fri, 28 Jun 2019, 14:09:30 EST Fri, 28 Jun 2019, 15:37:11 EST Fri, 28 Jun 2019, 15:49:23 EST Thu, 15 Oct 2020, 11:09:31 EST Tue, 20 Oct 2020, 12:02:10 EST Tue, 20 Oct 2020, 12:05:22 EST Sat, 07 Nov 2020, 01:30:36 EST Filtered Full Citation counts:   Cited 4 times in TR Web of Science Cited 5 times in Scopus Search Google Scholar Access Statistics: 51 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Fri, 28 Jun 2019, 14:09:30 EST

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