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In this study, a novel architecture based on deep learning was developed to automatically detect tree crowns and estimate crown sizes and tree heights from a set of red\u2010green\u2010blue (RGB) images. The feasibility of the architecture was verified based on high\u2010resolution unmanned aerial vehicle (UAV) images using a neural network called FPN\u2010Faster R\u2010CNN, which is a unified network combining a feature pyramid network (FPN) and a faster region\u2010based convolutional neural network (Faster R\u2010CNN). Among more than 400 tree crowns, including 213 crowns of <jats:italic>Ginkgo biloba<\/jats:italic>, in 7 complex test scenes, 174 ginkgo tree crowns were correctly identified, yielding a recall level of 0.82. The precision and <jats:italic>F<\/jats:italic>\u2010score were 0.96 and 0.88, respectively. The mean absolute error (MAE) and mean absolute percentage error (MAPE) of crown width estimation were 0.37\u2009m and 8.71%, respectively. The MAE and MAPE of tree height estimation were 0.68\u2009m and 7.33%, respectively. The results showed that the architecture is practical and can be applied to many complex urban scenes to meet the needs of urban green space inventory management.<\/jats:p>","DOI":"10.1155\/2021\/6668934","type":"journal-article","created":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T23:39:31Z","timestamp":1628293171000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Automatic Detection and Parameter Estimation of <i>Ginkgo biloba<\/i> in Urban Environment Based on RGB Images"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3572-5266","authenticated-orcid":false,"given":"Kai","family":"Xia","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2972-9949","authenticated-orcid":false,"given":"Hao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0100-1780","authenticated-orcid":false,"given":"Yinhui","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0562-3499","authenticated-orcid":false,"given":"Xiaochen","family":"Du","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2734-480X","authenticated-orcid":false,"given":"Hailin","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,8,6]]},"reference":[{"key":"e_1_2_9_1_2","article-title":"Urban forestry revisited","volume":"44","author":"Kuchelmeister G.","year":"1993","journal-title":"Unasylva"},{"key":"e_1_2_9_2_2","volume-title":"Chicago\u2019s Urban Forest Ecosystem: Results of the Chicago Urban Forest Climate Project","author":"McPherson E. 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