{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T10:06:32Z","timestamp":1756461992872,"version":"3.28.0"},"reference-count":34,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,5]]},"DOI":"10.1109\/icra40945.2020.9196560","type":"proceedings-article","created":{"date-parts":[[2020,9,15]],"date-time":"2020-09-15T17:25:46Z","timestamp":1600190746000},"page":"371-377","source":"Crossref","is-referenced-by-count":29,"title":["Temporal Segmentation of Surgical Sub-tasks through Deep Learning with Multiple Data Sources"],"prefix":"10.1109","author":[{"given":"Yidan","family":"Qin","sequence":"first","affiliation":[]},{"given":"Sahba Aghajani","family":"Pedram","sequence":"additional","affiliation":[]},{"given":"Seyedshams","family":"Feyzabadi","sequence":"additional","affiliation":[]},{"given":"Max","family":"Allan","sequence":"additional","affiliation":[]},{"given":"A. Jonathan","family":"McLeod","sequence":"additional","affiliation":[]},{"given":"Joel W.","family":"Burdick","sequence":"additional","affiliation":[]},{"given":"Mahdi","family":"Azizian","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","first-page":"707","article-title":"Binary codes capable of correcting deletions, insertions, and reversals","volume":"10","author":"levenshtein","year":"1966","journal-title":"Soviet Physics Doklady"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(96)00142-2"},{"journal-title":"Machine Learning A Probabilistic Perspective","year":"2012","author":"murphy","key":"ref31"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2000.861302"},{"key":"ref34","first-page":"3","article-title":"Jhu-isi gesture and skill assessment working set (jigsaws): A surgical activity dataset for human motion modeling","volume":"3","author":"gao","year":"2014","journal-title":"MICCAI Workshop M2CAI"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-017-1600-y"},{"article-title":"Less is more: surgical phase recognition with less annotations through self-supervised pre-training of cnn-lstm networks","year":"2018","author":"yengera","key":"ref11"},{"key":"ref12","first-page":"167","article-title":"Sparse hidden markov models for surgical gesture classification and skill evaluation","author":"tao","year":"2012","journal-title":"International Conference on Information Processing in Computer-Assisted Interventions"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2005.869771"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989093"},{"key":"ref15","first-page":"339","article-title":"Surgical gesture segmentation and recognition","author":"tao","year":"2013","journal-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2013.04.007"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-60916-4_6"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793696"},{"key":"ref19","first-page":"47","article-title":"Temporal convolutional networks: A unified approach to action segmentation","author":"lea","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref28","first-page":"807","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"Proceedings of the 27th International Conference on Machine Learning (ICML-10)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00937-3_32"},{"article-title":"Very deep convolutional networks for large-scale image recognition","year":"2014","author":"simonyan","key":"ref27"},{"key":"ref3","article-title":"Interactive user interfaces for minimally invasive telesurgical systems","author":"dimaio","year":"2018","journal-title":"US Patent App"},{"key":"ref6","first-page":"551","article-title":"Recognizing surgical activities with recurrent neural networks","author":"dipietro","year":"2016","journal-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention"},{"article-title":"Adam: A method for stochastic optimization","year":"2014","author":"kingma","key":"ref29"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487305"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00174"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ISMR.2019.8710178"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IRC.2018.00011"},{"article-title":"Learning from a tiny dataset of manual annotations: a teacher\/student approach for surgical phase recognition","year":"2018","author":"yu","key":"ref9"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1002\/rcs.408"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-019-01953-x"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2787657"},{"key":"ref21","first-page":"36","article-title":"Segmental spatiotemporal cnns for fine-grained action segmentation","author":"lea","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref24","first-page":"961","article-title":"Activitynet: A large-scale video benchmark for human activity understanding","author":"caba heilbron","year":"2015","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"article-title":"Tricornet: A hybrid temporal convolutional and recurrent network for video action segmentation","year":"2017","author":"ding","key":"ref23"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2593957"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2016.2647680"}],"event":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","start":{"date-parts":[[2020,5,31]]},"location":"Paris, France","end":{"date-parts":[[2020,8,31]]}},"container-title":["2020 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9187508\/9196508\/09196560.pdf?arnumber=9196560","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T20:24:54Z","timestamp":1656361494000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9196560\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/icra40945.2020.9196560","relation":{},"subject":[],"published":{"date-parts":[[2020,5]]}}}