{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T03:07:43Z","timestamp":1784776063848,"version":"3.55.0"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T00:00:00Z","timestamp":1656201600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T00:00:00Z","timestamp":1656201600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100018876","name":"National Centre for Nuclear Robotics","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100018876","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,6,26]]},"DOI":"10.1109\/ivmsp54334.2022.9816220","type":"proceedings-article","created":{"date-parts":[[2022,7,11]],"date-time":"2022-07-11T20:02:00Z","timestamp":1657569720000},"page":"1-5","source":"Crossref","is-referenced-by-count":30,"title":["Drone Footage Wind Turbine Surface Damage Detection"],"prefix":"10.1109","author":[{"given":"Ashley","family":"Foster","sequence":"first","affiliation":[{"name":"University of Plymouth,School of Engineering, Computing and Mathematics (SeCAM),UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oscar","family":"Best","sequence":"additional","affiliation":[{"name":"University of Plymouth,School of Engineering, Computing and Mathematics (SeCAM),UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mario","family":"Gianni","sequence":"additional","affiliation":[{"name":"University of Plymouth,School of Engineering, Computing and Mathematics (SeCAM),UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Asiya","family":"Khan","sequence":"additional","affiliation":[{"name":"University of Plymouth,School of Engineering, Computing and Mathematics (SeCAM),UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keri","family":"Collins","sequence":"additional","affiliation":[{"name":"University of Plymouth,School of Engineering, Computing and Mathematics (SeCAM),UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanjay","family":"Sharma","sequence":"additional","affiliation":[{"name":"University of Plymouth,School of Engineering, Computing and Mathematics (SeCAM),UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","article-title":"Wind turbine, close up with drone. watch in 1080p!!!","author":"n\u00f8hr","year":"2015"},{"key":"ref32","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-10602-1_48","article-title":"Microsoft coco: Common objects in context","author":"lin","year":"2014"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3390\/electronics10161973"},{"key":"ref30","article-title":"Yolov4: Optimal speed and accuracy of object detection","author":"bochkovskiy","year":"2020"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref35","article-title":"Faster r-cnn resnet-101-c4 wind turbine surface damage detection","author":"foster","year":"2021"},{"key":"ref34","article-title":"Yolov5s wind turbine surface damage object detection","author":"foster","year":"2021"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.procir.2019.03.286"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICEEE.2018.8533924"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-02587-7"},{"key":"ref13","article-title":"YOLO Annotated Wind Turbine Surface Damage","author":"foster","year":"2021"},{"key":"ref14","article-title":"Dtu - drone inspection images of wind turbine","author":"shihavuddin","year":"2018"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3000506"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1177\/16878132221081580"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref18","article-title":"Deep residual learning for image recognition","volume":"abs 1512 3385","author":"he","year":"2015","journal-title":"CoRR"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.18178\/ijmerr.8.6.830-838"},{"key":"ref27","article-title":"Detectron2","author":"wu","year":"2019"},{"key":"ref3","article-title":"Calexico man identified as victim of fatal 100-foot fall inside whitewater turbine","year":"2021"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.joule.2019.11.012"},{"key":"ref29","article-title":"An end-to-end steel surface defect detection approach via fusing multiple hierarchical features","author":"he","year":"2019"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ECMR50962.2021.9568790"},{"key":"ref8","article-title":"Combining weakly and strongly supervised segmentation methods for wind turbine damage annotation","author":"crous","year":"2018","journal-title":"Computer Science"},{"key":"ref7","article-title":"Net Zero Strategy: Build Back Greener","year":"2021"},{"key":"ref2","article-title":"Finnish worker dies in sirdal accident","year":"2021"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.3390\/en12040676"},{"key":"ref1","article-title":"Big spring man accidentally falls off wind turbine; dies","year":"2021"},{"key":"ref20","article-title":"Microsoft coco: Common objects in context","author":"lin","year":"2015"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1038\/35083698"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging7030046"},{"key":"ref24","first-page":"1","article-title":"Lightning damage to wind turbine blades from wind farms in u.s","volume":"31","author":"garolera","year":"2014","journal-title":"IEEE Transactions on Power Delivery"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2019.109382"},{"key":"ref26","article-title":"Deep residual learning for image recognition","author":"he","year":"2015"},{"key":"ref25","article-title":"Make Sense","author":"skalski","year":"2019"}],"event":{"name":"2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)","location":"Nafplio, Greece","start":{"date-parts":[[2022,6,26]]},"end":{"date-parts":[[2022,6,29]]}},"container-title":["2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9816065\/9816173\/09816220.pdf?arnumber=9816220","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,5]],"date-time":"2022-08-05T00:43:10Z","timestamp":1659660190000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9816220\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,26]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/ivmsp54334.2022.9816220","relation":{},"subject":[],"published":{"date-parts":[[2022,6,26]]}}}