Automatic driver stress level classification using multimodal deep learning Rastgoo, Mohammad Naim, Nakisa, Bahareh, Maire, Frederic, Rakotonirainy, Andry and Chandran, Vinod 2019, Automatic driver stress level classification using multimodal deep learning, Expert Systems with Applications, vol. 138, pp. 1-11, doi: 10.1016/j.eswa.2019.07.010. Attached Files Name Description MIMEType Size Downloads Title Automatic driver stress level classification using multimodal deep learning Author(s) Rastgoo, Mohammad Naim Nakisa, Bahareh Maire, Frederic Rakotonirainy, Andry Chandran, Vinod Journal name Expert Systems with Applications Volume number 138 Article ID 112793 Start page 1 End page 11 Total pages 11 Publisher Elsevier Place of publication Amsterdam, The Netherlands Publication date 2019-12-30 ISSN 0957-4174 Keyword(s) Deep learning Driver stress detection Convolutional neural network Long short term memory ECG signal Vehicle data Language eng DOI 10.1016/j.eswa.2019.07.010 Indigenous content off Field of Research 01 Mathematical Sciences 08 Information and Computing Sciences HERDC Research category C1.1 Refereed article in a scholarly journal Persistent URL http://hdl.handle.net/10536/DRO/DU:30130597 Document type: Journal Article 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, 10 Oct 2019, 09:54:24 EST Thu, 10 Oct 2019, 10:51:51 EST Fri, 11 Oct 2019, 04:00:32 EST Fri, 11 Oct 2019, 05:03:41 EST Fri, 18 Oct 2019, 11:14:04 EST Fri, 18 Oct 2019, 11:16:05 EST Sat, 05 Sep 2020, 02:40:31 EST Filtered Full Citation counts:   Cited 3 times in TR Web of Science Cited 4 times in Scopus Search Google Scholar Access Statistics: 126 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Thu, 10 Oct 2019, 10:51:51 EST

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