{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T15:40:04Z","timestamp":1779291604996,"version":"3.51.4"},"reference-count":30,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,9,3]],"date-time":"2022-09-03T00:00:00Z","timestamp":1662163200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of China","award":["U1809208"],"award-info":[{"award-number":["U1809208"]}]},{"name":"Natural Science Foundation of China","award":["2021C02005"],"award-info":[{"award-number":["2021C02005"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["U1809208"],"award-info":[{"award-number":["U1809208"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["2021C02005"],"award-info":[{"award-number":["2021C02005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Semantic segmentation of standing trees is important to obtain factors of standing trees from images automatically and effectively. Aiming at the accurate segmentation of multiple standing trees in complex backgrounds, some traditional methods have shortcomings such as low segmentation accuracy and manual intervention. To achieve accurate segmentation of standing tree images effectively, SEMD, a lightweight network segmentation model based on deep learning, is proposed in this article. DeepLabV3+ is chosen as the base framework to perform multi-scale fusion of the convolutional features of the standing trees in images, so as to reduce the loss of image edge details during the standing tree segmentation and reduce the loss of feature information. MobileNet, a lightweight network, is integrated into the backbone network to reduce the computational complexity. Furthermore, SENet, an attention mechanism, is added to obtain the feature information efficiently and suppress the generation of useless feature information. The extensive experimental results show that using the SEMD model the MIoU of the semantic segmentation of standing tree images of different varieties and categories under simple and complex backgrounds reaches 91.78% and 86.90%, respectively. The lightweight network segmentation model SEMD based on deep learning proposed in this paper can solve the problem of multiple standing trees segmentation with high accuracy.<\/jats:p>","DOI":"10.3390\/s22176663","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:18:32Z","timestamp":1662610712000},"page":"6663","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Automatic Segmentation of Standing Trees from Forest Images Based on Deep Learning"],"prefix":"10.3390","volume":"22","author":[{"given":"Lijuan","family":"Shi","sequence":"first","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoying","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lufeng","family":"Mo","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaomei","family":"Yi","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoping","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Huzhou University, Huzhou 313000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8946-3447","authenticated-orcid":false,"given":"Peng","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.isprsjprs.2017.02.011","article-title":"Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery","volume":"126","author":"Dechesne","year":"2017","journal-title":"ISPRS J. 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