基于PointCNN和3DmFV-Net两种深度神经网络的激光雷达点云树种和枯死树分类

IF 2.1 4区地球科学 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

PFG-Journal of Photogrammetry Remote Sensing and Geoinformation Science Pub Date : 2022-03-30 DOI:10.1007/s41064-022-00200-4

Maximilian Hell, M. Brandmeier, S. Briechle, P. Krzystek

引用次数: 7

摘要

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Classification of Tree Species and Standing Dead Trees with Lidar Point Clouds Using Two Deep Neural Networks: PointCNN and 3DmFV-Net

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来源期刊

PFG-Journal of Photogrammetry Remote Sensing and Geoinformation Science Physics and Astronomy-Instrumentation

CiteScore

8.20

自引率

2.40%

发文量

期刊介绍： PFG is an international scholarly journal covering the progress and application of photogrammetric methods, remote sensing technology and the interconnected field of geoinformation science. It places special editorial emphasis on the communication of new methodologies in data acquisition and new approaches to optimized processing and interpretation of all types of data which were acquired by photogrammetric methods, remote sensing, image processing and the computer-aided interpretation of such data in general. The journal hence addresses both researchers and students of these disciplines at academic institutions and universities as well as the downstream users in both the private sector and public administration. Founded in 1926 under the former name Bildmessung und Luftbildwesen, PFG is worldwide the oldest journal on photogrammetry. It is the official journal of the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF).