{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T11:55:31Z","timestamp":1784116531729,"version":"3.55.0"},"reference-count":48,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1109\/bigdata.2018.8621990","type":"proceedings-article","created":{"date-parts":[[2019,1,24]],"date-time":"2019-01-24T22:07:18Z","timestamp":1548367638000},"page":"1367-1376","source":"Crossref","is-referenced-by-count":178,"title":["Transfer learning for time series classification"],"prefix":"10.1109","author":[{"given":"Hassan","family":"Ismail Fawaz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Germain","family":"Forestier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan","family":"Weber","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lhassane","family":"Idoumghar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre-Alain","family":"Muller","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume":"9","author":"glorot","year":"2010","journal-title":"International Conference on Artificial Intelligence and Statistics"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2015.06.034"},{"key":"ref32","article-title":"Transfer Learning for Time Series Classification in Dissimilarity Spaces","author":"spiegel","year":"2016","journal-title":"European conference on machine learning and principles and practice of knowledge discovery in databases"},{"key":"ref31","first-page":"27","article-title":"Transfer Learning for Time Series Anomaly Detection","author":"vercruyssen","year":"2017","journal-title":"Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases"},{"key":"ref30","first-page":"142","article-title":"Recognizing activities in multiple contexts using transfer learning","author":"kasteren","year":"2008","journal-title":"Association for the Advancement of Artificial Intelligence - AI in Elder care"},{"key":"ref37","first-page":"448","article-title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","author":"ioffe","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-016-0483-9"},{"key":"ref35","article-title":"Towards a universal neural network encoder for time series","author":"serr\u00e0","year":"2018","journal-title":"ArXiv"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.10"},{"key":"ref10","article-title":"Multi-Scale Convolutional Neural Networks for Time Series Classification","author":"cui","year":"2016","journal-title":"ArXiv"},{"key":"ref40","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"International Conference on Learning Representations"},{"key":"ref11","article-title":"Deep Learning for Time-Series Analysis","author":"cristian borges gamboa","year":"2017","journal-title":"ArXiv"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557122"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623613"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-016-0043-6"},{"key":"ref15","first-page":"1097","article-title":"ImageNet Classification with Deep Convolutional Neural Networks","author":"krizhevsky","year":"2012","journal-title":"Advances in Neural Information Processing Systems 25"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref18","first-page":"3104","article-title":"Sequence to Sequence Learning with Neural Networks","author":"sutskever","year":"2014","journal-title":"Neural Information Processing Systems"},{"key":"ref19","article-title":"Neural Machine Translation by Jointly Learning to Align and Translate","author":"bahdanau","year":"0"},{"key":"ref28","first-page":"97","article-title":"Learning Transferable Features with Deep Adaptation Networks","volume":"37","author":"long","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref4","article-title":"Understanding deep learning requires rethinking generalization","author":"zhang","year":"2016","journal-title":"ArXiv"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2416723"},{"key":"ref6","first-page":"3320","article-title":"How transferable are features in deep neural networks?","author":"yosinski","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3137133.3137146"},{"key":"ref5","article-title":"Data augmentation using synthetic data for time series classification with deep residual networks","author":"ismail fawaz","year":"2018","journal-title":"International Workshop on Advanced Analytics and Learning on Temporal Data ECML PKDD"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref7","article-title":"Domain Adaptation for Visual Applications: A Comprehensive Survey","author":"csurka","year":"2017","journal-title":"ArXiv e-prints"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966039"},{"key":"ref9","article-title":"OpenImages: A public dataset for large-scale multi- label and multi-class image classification","author":"krasin","year":"2017"},{"key":"ref1","article-title":"The UCR Time Series Classification Archive","author":"chen","year":"2015"},{"key":"ref46","first-page":"265","article-title":"TensorFlow: A System for Large- scale Machine Learning","author":"abadi","year":"2016","journal-title":"USENIX Conference on Operating Systems Design and Implementation"},{"key":"ref20","article-title":"Cost-Sensitive Convolution based Neural Networks for Imbalanced Time-Series Classification","author":"geng","year":"2018","journal-title":"ArXiv e-prints"},{"key":"ref45","article-title":"Keras","author":"chollet","year":"2015"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.106"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2014.01.008"},{"key":"ref47","first-page":"917","article-title":"Judicious setting of dynamic time warping&#x2019;s window width allows more accurate classification of time series","author":"dau","year":"2017","journal-title":"IEEE International Conference on Big Data"},{"key":"ref21","article-title":"Data Augmentation for Time Series Classification using Convolutional Neural Networks","author":"le guennec","year":"2016","journal-title":"ECME\/PKDD Workshop on Advanced Analytics and Learning on Temporal Data"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2011.09.029"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.03.056"},{"key":"ref41","first-page":"2318","article-title":"Transfer Learning to Predict Missing Ratings via Heterogeneous User Feedbacks","author":"pan","year":"2011","journal-title":"International Joint Conference on Artificial Intelligence"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.80"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2010.09.013"},{"key":"ref26","article-title":"Deep learning for time series classification: a review","author":"ismail fawaz","year":"2018","journal-title":"ArXiv"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2014.27"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.93"}],"event":{"name":"2018 IEEE International Conference on Big Data (Big Data)","location":"Seattle, WA, USA","start":{"date-parts":[[2018,12,10]]},"end":{"date-parts":[[2018,12,13]]}},"container-title":["2018 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8610059\/8621858\/08621990.pdf?arnumber=8621990","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T18:56:59Z","timestamp":1643223419000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8621990\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12]]},"references-count":48,"URL":"https:\/\/doi.org\/10.1109\/bigdata.2018.8621990","relation":{},"subject":[],"published":{"date-parts":[[2018,12]]}}}