Detection and Quantification of <i>Arnica montana</i> L. Inflorescences in Grassland Ecosystems Using Convolutional Neural Networks and Drone-Based Remote Sensing

Detection and Quantification of <i>Arnica montana</i> L. Inflorescences in Grassland Ecosystems Using Convolutional Neural Networks and Drone-Based Remote Sensing

<i>Arnica montana</i> L. is a medicinal plant with significant conservation importance. It is crucial to monitor this species, ensuring its sustainable harvesting and management. The aim of this study is to develop a practical system that can effectively detect <i>A. montana</i&...

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Bibliographic Details
Main Authors: Dragomir D. Sângeorzan, Florin Păcurar, Albert Reif, Holger Weinacker, Evelyn Rușdea, Ioana Vaida, Ioan Rotar
Format: Article
Language:English
Published: MDPI AG 2024-06-01
Series:Remote Sensing
Subjects:
<i>Arnica</i>
UAV
low resolution
ground sampling distance
inflorescence counting
ResNet
Online Access:https://www.mdpi.com/2072-4292/16/11/2012

Internet

https://www.mdpi.com/2072-4292/16/11/2012

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