{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T04:49:18Z","timestamp":1746766158776,"version":"3.28.0"},"reference-count":27,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"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":[[2021,12,15]]},"DOI":"10.1109\/bigdata52589.2021.9671701","type":"proceedings-article","created":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T20:39:16Z","timestamp":1642106356000},"page":"4491-4495","source":"Crossref","is-referenced-by-count":4,"title":["Deep Learning Approach Towards Squat Isolation in a Multi-Embedded Track Geometry Defects"],"prefix":"10.1109","author":[{"given":"Ibrahim","family":"Balogun","sequence":"first","affiliation":[]},{"given":"Mark","family":"Leadingham","sequence":"additional","affiliation":[]},{"given":"Dominique","family":"Gulliot","sequence":"additional","affiliation":[]},{"given":"Nii","family":"Attoh-Okine","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2016.7727522"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2016.07.014"},{"key":"ref12","first-page":"91105","article-title":"The recent applications of machine learning in rail track maintenance: A survey","author":"nakhaee","year":"2019","journal-title":"International Conference on Reliability Safety and Security of Railway Systems"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.5604\/08669546.1160926"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2017.04.032"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1289\/EHP4713"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1167\/9.8.1037"},{"article-title":"Very deep convolutional networks for large-scale image recognition","year":"2014","author":"simonyan","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3383972.3383975"},{"key":"ref19","first-page":"120","article-title":"The opencv library","volume":"25","author":"bradski","year":"2000","journal-title":"Dr Dobb&#x2019;s J Softw Tools"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1061\/JTEPBS.0000408"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2020.107359"},{"article-title":"Image Segmentation with Mask R-CNN, GrabCut, and OpenCV","year":"2020","author":"rosebrock","key":"ref27"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2016.12.012"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1177\/0954409717721870"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1186\/s13640-017-0241-y"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2019.107246"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1080\/23248378.2018.1550626"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2018.00235"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2984264"},{"article-title":"Digital image processing","year":"2002","author":"gonzalez","key":"ref20"},{"article-title":"On the relationship between track geometry defects and development of internal rail defects","year":"2015","author":"zarembski","key":"ref22"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1061\/AJRUA6.0001141"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2019.00060"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1115\/1.4051597"},{"article-title":"Image data of insulation joints - ProRail","year":"2017","author":"hees","key":"ref26"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2016.12.012"}],"event":{"name":"2021 IEEE International Conference on Big Data (Big Data)","start":{"date-parts":[[2021,12,15]]},"location":"Orlando, FL, USA","end":{"date-parts":[[2021,12,18]]}},"container-title":["2021 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9671263\/9671273\/09671701.pdf?arnumber=9671701","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:55:20Z","timestamp":1652201720000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9671701\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,15]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/bigdata52589.2021.9671701","relation":{},"subject":[],"published":{"date-parts":[[2021,12,15]]}}}