{"id":1448,"date":"2022-09-05T20:40:13","date_gmt":"2022-09-05T20:40:13","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=1448"},"modified":"2022-09-05T21:15:43","modified_gmt":"2022-09-05T21:15:43","slug":"vol19-no2-art1","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no2\/vol19-no2-art1\/","title":{"rendered":"Detection and Segmentation of Damaged Photovoltaic Panels Using Deep Learning and Fine-tuning in Images Captured by Drone"},"content":{"rendered":"<p>Lu\u00eds Fabr\u00edcio de Freitas Souza <a href=\"https:\/\/orcid.org\/0000-0002-3156-1359\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Tassiana Marinho de Castro <a href=\"https:\/\/orcid.org\/0000-0003-1369-4964\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Lucas de Oliveira Santos <a href=\"https:\/\/orcid.org\/0000-0002-9388-8146\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Adriell Gomes Marques <a href=\"https:\/\/orcid.org\/0000-0001-6274-1961\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Jos\u00e9 Jerovane da Costa Nascimento <a href=\"https:\/\/orcid.org\/0000-0002-7361-4316\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Matheus Ara\u00fajo dos Santos <a href=\"https:\/\/orcid.org\/0000-0003-3854-7178\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Guilherme F. Brilhante Severiano <a href=\"https:\/\/orcid.org\/0000-0002-7109-7220\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, &#038; Pedro Pedrosa Rebou\u00e7as Filho <a href=\"https:\/\/orcid.org\/0000-0002-1878-5489\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a><\/p>\n<p><strong>Abstract:<\/strong> Energy consumption is a direct impact factor in various sectors of society. Different technologies for energy generation are based on renewable sources and used as alternatives to the consumption of finite resources. Among these technologies, photovoltaic panels represent an efficient solution for energy generation and an option for sustainable consumption. The problem of damaged panels brings numerous problems in energy generation, from the interruption of generation to losses through financial investments. The proposed study presents an efficient model based on deep learning for detection and different models based on fine-tuning for the segmentation of damaged photovoltaic panels. The use of the Detectron2 convolutional network obtained 78% of Accuracy for detection and 95% precision in the detectable panels, also obtaining 99.91% for the segmentation problem of photovoltaic panels in the best-generated model in this study. The proposed model showed great effectiveness for panel detection and segmentation, surpassing works found in the literature.<\/p>\n<p><strong>Keywords:<\/strong> Photovoltaic Panels, Deep Learning for Detection, Panel Segmentation, Detectron2.<\/p>\n<p><strong>DOI code:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol19-no2-art1\">10.21528\/lnlm-vol19-no2-art1<\/a><\/p>\n<p><strong>PDF file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/12\/vol19-no2-art1.pdf\">vol19-no2-art1.pdf<\/a><\/p>\n<p><strong>BibTex file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/12\/vol19-no2-art1.bib\">vol19-no2-art1.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Lu\u00eds Fabr\u00edcio de Freitas Souza , Tassiana Marinho de Castro , Lucas de Oliveira Santos , Adriell Gomes Marques , Jos\u00e9 Jerovane da Costa Nascimento , Matheus Ara\u00fajo dos Santos , Guilherme F. Brilhante Severiano , &#038; Pedro Pedrosa Rebou\u00e7as <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no2\/vol19-no2-art1\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1443,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1448","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Detection and Segmentation of Damaged Photovoltaic Panels Using Deep Learning and Fine-tuning in Images Captured by Drone - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol19-no2\/vol19-no2-art1\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Detection and Segmentation of Damaged Photovoltaic Panels Using Deep Learning and Fine-tuning in Images Captured by Drone - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"Lu\u00eds Fabr\u00edcio de Freitas Souza , Tassiana Marinho de Castro , Lucas de Oliveira Santos , Adriell Gomes Marques , Jos\u00e9 Jerovane da Costa Nascimento , Matheus Ara\u00fajo dos Santos , Guilherme F. 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