{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,2]],"date-time":"2025-07-02T10:45:54Z","timestamp":1751453154354,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030918842"},{"type":"electronic","value":"9783030918859"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-91885-9_32","type":"book-chapter","created":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T13:03:12Z","timestamp":1638450192000},"page":"430-443","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Artificial Intelligence Architecture Based on\u00a0Planar LiDAR Scan Data to\u00a0Detect Energy Pylon Structures in\u00a0a\u00a0UAV Autonomous Detailed Inspection Process"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4917-316X","authenticated-orcid":false,"given":"Matheus F.","family":"Ferraz","sequence":"first","affiliation":[]},{"given":"Luciano B.","family":"J\u00fanior","sequence":"additional","affiliation":[]},{"given":"Aroldo S. K.","family":"Komori","sequence":"additional","affiliation":[]},{"given":"Lucas C.","family":"Rech","sequence":"additional","affiliation":[]},{"given":"Guilherme H. T.","family":"Schneider","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4100-1494","authenticated-orcid":false,"given":"Guido S.","family":"Berger","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5930-2140","authenticated-orcid":false,"given":"\u00c1lvaro R.","family":"Cantieri","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7902-1207","authenticated-orcid":false,"given":"Jos\u00e9","family":"Lima","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1415-5527","authenticated-orcid":false,"given":"Marco A.","family":"Wehrmeister","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,1]]},"reference":[{"key":"32_CR1","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1016\/j.eswa.2017.09.033","volume":"92","author":"A Al-Kaff","year":"2018","unstructured":"Al-Kaff, A., Mart\u00edn, D., Garc\u00eda, F., de la Escalera, A., Mar\u00eda Armingol, J.: Survey of computer vision algorithms and applications for unmanned aerial vehicles. Expert Syst. Appl. 92, 447\u2013463 (2018)","journal-title":"Expert Syst. Appl."},{"key":"32_CR2","doi-asserted-by":"publisher","unstructured":"Araar, O., Aouf, N.: Visual servoing of a Quadrotor UAV for autonomous power lines inspection. In: 2014 22nd Mediterranean Conference on Control and Automation, MED 2014 (June), pp. 1418\u20131424 (2014). https:\/\/doi.org\/10.1109\/MED.2014.6961575","DOI":"10.1109\/MED.2014.6961575"},{"issue":"3","key":"32_CR3","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1108\/IR-11-2014-0419","volume":"42","author":"O Araar","year":"2015","unstructured":"Araar, O., Aouf, N., Dietz, J.L.V.: Power pylon detection and monocular depth estimation from inspection UAVs. Ind. Robot. 42(3), 200\u2013213 (2015). https:\/\/doi.org\/10.1108\/IR-11-2014-0419","journal-title":"Ind. Robot."},{"issue":"8","key":"32_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/s19081812","volume":"19","author":"F Azevedo","year":"2019","unstructured":"Azevedo, F.: LiDAR-based real-time detection and modeling of power lines for unmanned aerial vehicles. Sensors (Switzerland) 19(8), 1\u201328 (2019). https:\/\/doi.org\/10.3390\/s19081812","journal-title":"Sensors (Switzerland)"},{"key":"32_CR5","doi-asserted-by":"publisher","unstructured":"Bian, J., Hui, X., Zhao, X., Tan, M.: A point-line-based SLAM framework for UAV close proximity transmission tower inspection. In: 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018, pp. 1016\u20131021 (2019). https:\/\/doi.org\/10.1109\/ROBIO.2018.8664716","DOI":"10.1109\/ROBIO.2018.8664716"},{"issue":"2","key":"32_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1177\/1729881418763452","volume":"15","author":"A Cer\u00f3n","year":"2018","unstructured":"Cer\u00f3n, A., Mondrag\u00f3n, I., Prieto, F.: Onboard visual-based navigation system for power line following with UAV. Int. J. Adv. Rob. Syst. 15(2), 1\u201312 (2018). https:\/\/doi.org\/10.1177\/1729881418763452","journal-title":"Int. J. Adv. Rob. Syst."},{"key":"32_CR7","unstructured":"GRABCAD: GrabCAD (2021). https:\/\/grabcad.com\/"},{"key":"32_CR8","doi-asserted-by":"publisher","unstructured":"Hui, X., Bian, J., Yu, Y., Zhao, X., Tan, M.: A novel autonomous navigation approach for UAV power line inspection. In: 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017, 1\u20136 January 2018 (2018). https:\/\/doi.org\/10.1109\/ROBIO.2017.8324488","DOI":"10.1109\/ROBIO.2017.8324488"},{"issue":"5","key":"32_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1088\/1757-899X\/382\/5\/052025","volume":"382","author":"X Li","year":"2018","unstructured":"Li, X., Guo, Y.: Application of LiDAR technology in power line inspection. IOP Conf. Ser.: Mater. Sci. Eng. 382(5), 1\u20135 (2018). https:\/\/doi.org\/10.1088\/1757-899X\/382\/5\/052025","journal-title":"IOP Conf. Ser.: Mater. Sci. Eng."},{"issue":"7","key":"32_CR10","doi-asserted-by":"publisher","first-page":"14887","DOI":"10.3390\/s150714887","volume":"15","author":"K M\u00e1th\u00e9","year":"2015","unstructured":"M\u00e1th\u00e9, K., Bu\u015foniu, L.: Vision and control for UAVs: a survey of general methods and of inexpensive platforms for infrastructure inspection. Sensors (Switzerland) 15(7), 14887\u201314916 (2015)","journal-title":"Sensors (Switzerland)"},{"key":"32_CR11","doi-asserted-by":"publisher","unstructured":"Men\u00e9ndez, O., P\u00e9rez, M., Cheein, F.A.: Visual-based positioning of aerial maintenance platforms on overhead transmission lines. Appl. Sci. (Switz.) 9(1) (2019). https:\/\/doi.org\/10.3390\/app9010165","DOI":"10.3390\/app9010165"},{"issue":"January","key":"32_CR12","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.ijepes.2017.12.016","volume":"99","author":"VN Nguyen","year":"2018","unstructured":"Nguyen, V.N., Jenssen, R., Roverso, D.: Automatic autonomous vision-based power line inspection: a review of current status and the potential role of deep learning. Int. J. Electr. Power Energy Syst. 99(January), 107\u2013120 (2018)","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"32_CR13","doi-asserted-by":"publisher","unstructured":"Shuai, C., Wang, H., Zhang, G., Kou, Z., Zhang, W.: Power lines extraction and distance measurement from binocular aerial images for power lines inspection using UAV. In: Proceedings - 9th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2017, vol. 2, 69\u201374 (2017). https:\/\/doi.org\/10.1109\/IHMSC.2017.131","DOI":"10.1109\/IHMSC.2017.131"},{"key":"32_CR14","doi-asserted-by":"publisher","unstructured":"Tian, F., Wang, Y., Zhu, L.: Power line recognition and tracking method for UAVs inspection. In: 2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics (August), pp. 2136\u20132141 (2015). https:\/\/doi.org\/10.1109\/ICInfA.2015.7279641","DOI":"10.1109\/ICInfA.2015.7279641"},{"issue":"2","key":"32_CR15","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1177\/1756829317745316","volume":"10","author":"C Vi\u00f1a","year":"2018","unstructured":"Vi\u00f1a, C., Morin, P.: Micro air vehicle local pose estimation with a two-dimensional laser scanner: a case study for electric tower inspection. Int. J. Micro Air Veh. 10(2), 127\u2013156 (2018). https:\/\/doi.org\/10.1177\/1756829317745316","journal-title":"Int. J. Micro Air Veh."},{"key":"32_CR16","doi-asserted-by":"publisher","unstructured":"Wu, J., Fei, W., Li, Q.: An integrated measure and location method based on airborne 2D laser scanning sensor for UAV\u2019s power line inspection. In: Proceedings - 2013 5th Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2013, pp. 213\u2013217 (2013). https:\/\/doi.org\/10.1109\/ICMTMA.2013.58","DOI":"10.1109\/ICMTMA.2013.58"},{"key":"32_CR17","doi-asserted-by":"publisher","unstructured":"Zhang, W., et al.: The application research of UAV-based LiDAR system for power line inspection. In: Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017), vol. 74, pp. 962\u2013966 (2017). https:\/\/doi.org\/10.2991\/iccia-17.2017.174","DOI":"10.2991\/iccia-17.2017.174"},{"key":"32_CR18","doi-asserted-by":"publisher","unstructured":"Zhao, X., Tan, M., Hui, X., Bian, J.: Deep-learning-based autonomous navigation approach for UAV transmission line inspection. In: Proceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018, pp. 455\u2013460 (2018). https:\/\/doi.org\/10.1109\/ICACI.2018.8377502","DOI":"10.1109\/ICACI.2018.8377502"},{"key":"32_CR19","doi-asserted-by":"publisher","unstructured":"Zimmermann, F., Eling, C., Klingbeil, L., Kuhlmann, H.: Precise positioning of UAVs - dealing with challenging RTK-GPS measurement conditions during automated UAV flights. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 4(2W3), 95\u2013102 (2017). https:\/\/doi.org\/10.5194\/isprs-annals-IV-2-W3-95-2017","DOI":"10.5194\/isprs-annals-IV-2-W3-95-2017"}],"container-title":["Communications in Computer and Information Science","Optimization, Learning Algorithms and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-91885-9_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T13:26:37Z","timestamp":1638451597000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-91885-9_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030918842","9783030918859"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-91885-9_32","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"1 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"OL2A","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Optimization, Learning Algorithms and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bragan\u00e7a","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 July 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ol2a2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ol2a.ipb.pt\/EN_index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"134","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"29% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic the conference was held online.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}