{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,29]],"date-time":"2025-03-29T04:13:52Z","timestamp":1743221632087,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031734991"},{"type":"electronic","value":"9783031735004"}],"license":[{"start":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T00:00:00Z","timestamp":1731715200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T00:00:00Z","timestamp":1731715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-73500-4_16","type":"book-chapter","created":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T04:01:40Z","timestamp":1731643300000},"page":"184-196","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Assessing Advanced Computer Vision Techniques in\u00a0Aerial Imagery: A Case Study on\u00a0Transmission Tower Identification"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5363-3608","authenticated-orcid":false,"given":"Daniela L.","family":"Freire","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4765-6459","authenticated-orcid":false,"given":"Andre C. P. L. F.","family":"de Carvalho","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0575-9633","authenticated-orcid":false,"given":"Augusto Jos\u00e9","family":"Peterlevitz","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6933-213X","authenticated-orcid":false,"given":"Mateus Antonio","family":"Chinelatto","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8002-8411","authenticated-orcid":false,"given":"Ricardo Dutra","family":"da Silva","sequence":"additional","affiliation":[]},{"given":"Juan Fernando Rojas","family":"Perea","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,16]]},"reference":[{"key":"16_CR1","doi-asserted-by":"crossref","unstructured":"Luque-Vega, L.F., Castillo-Toledo, B., Loukianov, A., Gonzalez-Jimenez, L.E.: Power line inspection via an unmanned aerial system based on the quadrotor helicopter. In: MELECON 2014-2014 17th IEEE Mediterranean Electrotechnical Conference, pp. 393\u2013397. IEEE (2014)","DOI":"10.1109\/MELCON.2014.6820566"},{"key":"16_CR2","doi-asserted-by":"publisher","first-page":"110312","DOI":"10.1109\/ACCESS.2023.3322374","volume":"11","author":"AJ Peterlevitz","year":"2023","unstructured":"Peterlevitz, A.J., et al.: Sim-to-real transfer for object detection in aerial inspections of transmission towers. IEEE Access 11, 110312\u2013110327 (2023)","journal-title":"IEEE Access"},{"key":"16_CR3","doi-asserted-by":"crossref","unstructured":"Abdelfattah, R., Wang, X., Wang, S.: Ttpla: an aerial-image dataset for detection and segmentation of transmission towers and power lines. In: Proceedings of the Asian Conference on Computer Vision (2020)","DOI":"10.1007\/978-3-030-69544-6_36"},{"key":"16_CR4","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"16_CR5","doi-asserted-by":"publisher","first-page":"1066","DOI":"10.1016\/j.procs.2022.01.135","volume":"199","author":"P Jiang","year":"2022","unstructured":"Jiang, P., Ergu, D., Liu, F., Cai, Y., Ma, B.: A review of yolo algorithm developments. Procedia Comput. Sci. 199, 1066\u20131073 (2022)","journal-title":"Procedia Comput. Sci."},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Kirillov, A., et al.: Segment anything (2023)","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"16_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2021.3076050","volume":"60","author":"M Zand","year":"2021","unstructured":"Zand, M., Etemad, A., Greenspan, M.: Oriented bounding boxes for small and freely rotated objects. IEEE Trans. Geosci. Remote Sens. 60, 1\u201315 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"3","key":"16_CR8","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/JPROC.2023.3238524","volume":"111","author":"Z Zou","year":"2023","unstructured":"Zou, Z., Chen, K., Shi, Z., Guo, Y., Ye, J.: Object detection in 20 years: a survey. Proc. IEEE 111(3), 257\u2013276 (2023)","journal-title":"Proc. IEEE"},{"issue":"6","key":"16_CR9","doi-asserted-by":"publisher","first-page":"9243","DOI":"10.1007\/s11042-022-13644-y","volume":"82","author":"T Diwan","year":"2023","unstructured":"Diwan, T., Anirudh, G., Tembhurne, J.V.: Object detection using yolo: challenges, architectural successors, datasets and applications. Multimedia Tools Appl. 82(6), 9243\u20139275 (2023)","journal-title":"Multimedia Tools Appl."},{"issue":"2","key":"16_CR10","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.icte.2019.11.001","volume":"6","author":"Y Jamtsho","year":"2020","unstructured":"Jamtsho, Y., Riyamongkol, P., Waranusast, R.: Real-time bhutanese license plate localization using yolo. ICT Express 6(2), 121\u2013124 (2020)","journal-title":"ICT Express"},{"key":"16_CR11","unstructured":"Jocher, G., Chaurasia, A., Qiu, J.: Ultralytics yolov8 (2023). https:\/\/github.com\/ultralytics\/ultralytics"},{"key":"16_CR12","doi-asserted-by":"crossref","unstructured":"Wang, C.Y., Liao, H.Y.M.: YOLOv9: learning what you want to learn using programmable gradient information (2024)","DOI":"10.1007\/978-3-031-72751-1_1"},{"issue":"1","key":"16_CR13","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1038\/s41467-024-44824-z","volume":"15","author":"J Ma","year":"2024","unstructured":"Ma, J., He, Y., Li, F., Han, L., You, C., Wang, B.: Segment anything in medical images. Nat. Commun. 15(1), 654 (2024)","journal-title":"Nat. Commun."},{"key":"16_CR14","doi-asserted-by":"crossref","unstructured":"Ren, S., et al.: Segment anything, from space? In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 8355\u20138365 (2024)","DOI":"10.1109\/WACV57701.2024.00817"},{"key":"16_CR15","volume":"124","author":"LP Osco","year":"2023","unstructured":"Osco, L.P., et al.: The segment anything model (sam) for remote sensing applications: from zero to one shot. Int. J. Appl. Earth Obs. Geoinf. 124, 103540 (2023)","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"16_CR16","unstructured":"Zou, X., et al.: Segment everything everywhere all at once. In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. (eds.) Advances in Neural Information Processing Systems, vol.\u00a036, pp. 19769\u201319782. Curran Associates, Inc. (2023). https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2023\/file\/3ef61f7e4afacf9a2c5b71c726172b86-Paper-Conference.pdf"},{"issue":"4","key":"16_CR17","first-page":"4051","volume":"45","author":"F Pourpanah","year":"2022","unstructured":"Pourpanah, F., et al.: A review of generalized zero-shot learning methods. IEEE Trans. Pattern Anal. Mach. Intell. 45(4), 4051\u20134070 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"16_CR18","doi-asserted-by":"crossref","unstructured":"Menezes, A.G., Peterlevitz, A.J., Chinelatto, M.A., de\u00a0Carvalho, A.C.P.L.F.: Efficient parameter mining and freezing for continual object detection. In: Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2024, VISAPP, Rome, Italy, 27\u201329 February 2024, vol. 2, pp. 466\u2013474. SCITEPRESS (2024)","DOI":"10.5220\/0012362300003660"},{"key":"16_CR19","doi-asserted-by":"crossref","unstructured":"Zheng, Z., Wang, P., Liu, W., Li, J., Ye, R., Ren, D.: Distance-iou loss: faster and better learning for bounding box regression. In: Proceedings of th AAAI Conference on Artificial Intelligence, vol.\u00a034, pp. 12993\u201313000 (2020)","DOI":"10.1609\/aaai.v34i07.6999"},{"key":"16_CR20","unstructured":"Reis, D., Kupec, J., Hong, J., Daoudi, A.: Real-time flying object detection with yolov8. arXiv preprint arXiv:2305.09972 (2023)"},{"key":"16_CR21","first-page":"21002","volume":"33","author":"X Li","year":"2020","unstructured":"Li, X., et al.: Generalized focal loss: learning qualified and distributed bounding boxes for dense object detection. Adv. Neural. Inf. Process. Syst. 33, 21002\u201321012 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."}],"container-title":["Lecture Notes in Computer Science","Progress in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-73500-4_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T17:24:07Z","timestamp":1743182647000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73500-4_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,16]]},"ISBN":["9783031734991","9783031735004"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73500-4_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,16]]},"assertion":[{"value":"16 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EPIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"EPIA Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Viana do Castelo","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":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"epia2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/epia2024.pt","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}