首页|New Machine Learning Study Findings Has Been Reported by a Researcher at University of Applied Sciences and Arts (Enhancing Tree Species Identification in Forestry and Urban Forests through Light Detection and Ranging Point Cloud Structural ...)
New Machine Learning Study Findings Has Been Reported by a Researcher at University of Applied Sciences and Arts (Enhancing Tree Species Identification in Forestry and Urban Forests through Light Detection and Ranging Point Cloud Structural ...)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Mdpi
Research findings on artificial intelligence are discussed in a new report. According to news reporting originating from Gottingen, Germany, by NewsRx correspondents, research stated, “As remote sensing transforms forest and urban tree management, automating tree species classification is now a major challenge to harness these advances for forestry and urban management.” The news editors obtained a quote from the research from University of Applied Sciences and Arts: “This study investigated the use of structural bark features from terrestrial laser scanner point cloud data for tree species identification. It presents a novel mathematical approach for describing bark characteristics, which have traditionally been used by experts for the visual identification of tree species. These features were used to train four machine learning algorithms (decision trees, random forests, XGBoost, and support vector machines). These methods achieved high classification accuracies between 83% (decision tree) and 96% (XGBoost) with a data set of 85 trees of four species collected near Krakow, Poland.”
University of Applied Sciences and ArtsGottingenGermanyEuropeCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
Mdpi
