Comparison of Classical Methods and Mask R-CNN for Automatic Tree Detection and Mapping Using UAV Imagery

Detecting and mapping individual trees accurately and automatically from remote sensing images is of great significance for precision forest management. Many algorithms, including classical methods and deep learning techniques, have been developed and applied for tree crown detection from remote sen...

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Vydané v:	Remote sensing (Basel, Switzerland) Ročník 14; číslo 2; s. 295
Hlavní autori:	Yu, Kunyong, Hao, Zhenbang, Post, Christopher J., Mikhailova, Elena A., Lin, Lili, Zhao, Gejin, Tian, Shangfeng, Liu, Jian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.01.2022
Predmet:	Accuracy Aerial photography Algorithms Altitude Artificial neural networks canopy height Computer applications computers Data processing Deep learning Evaluation Forest management forest plantations Forestry Image segmentation LM algorithm Machine learning Mapping Mask R-CNN MCWS algorithm Model accuracy Multilayers Neural networks Parameter identification Plant species plantation forest Remote sensing Sensors Software Training tree crown Trees UAV imagery Unmanned aerial vehicles watersheds
ISSN:	2072-4292, 2072-4292
On-line prístup:	Získať plný text
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