{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/plad-a-dataset-for-multi-size-power-line","title":"STN PLAD: A Dataset for Multi-Size Power Line Assets Detection in High-Resolution UAV Images","arxiv_id":"2108.07944","date":"2021-08-18","proceeding":null,"authors":["André Luiz Buarque Vieira-e-Silva","Heitor Felix","Thiago de Menezes Chaves","Francisco Paulo Magalhães Simões","Veronica Teichrieb","Michel Mozinho dos Santos","Hemir da Cunha Santiago","Virginia Adélia Cordeiro Sgotti","Henrique Baptista Duffles Teixeira Lott Neto"],"abstract":"Many power line companies are using UAVs to perform their inspection processes instead of putting their workers at risk by making them climb high voltage power line towers, for instance. A crucial task for the inspection is to detect and classify assets in the power transmission lines. However, public data related to power line assets are scarce, preventing a faster evolution of this area. This work proposes the Power Line Assets Dataset, containing high-resolution and real-world images of multiple high-voltage power line components. It has 2,409 annotated objects divided into five classes: transmission tower, insulator, spacer, tower plate, and Stockbridge damper, which vary in size (resolution), orientation, illumination, angulation, and background. This work also presents an evaluation with popular deep object detection methods, showing considerable room for improvement. The STN PLAD dataset is publicly available at https://github.com/andreluizbvs/PLAD.","url_abs":"https://arxiv.org/abs/2108.07944v3","url_pdf":"https://arxiv.org/pdf/2108.07944v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"plad-a-dataset-for-multi-size-power-line","repo_url":"https://github.com/andreluizbvs/PLAD","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[{"slug":"plad","name":"STN PLAD","full_name":"STN Power Line Assets Dataset"}],"methods_introduced":[],"results":[{"leaderboard":"/sota/object-detection-on-plad","task":"Object Detection","dataset":"STN PLAD","model":"MS-PAD","rank_in_archive_order":1,"of":1,"metrics":{"mAP":"89.2%"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2108.07944","atlas_url":"https://app.syntology.ai/?focus=2108.07944","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}