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A Study on tree species discrimination using machine learning in forestry

机译:林业机器学习的树种辨别研究

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As the present state of forestry in Japan, the period of full-scale utilization of planted forests is approaching; consolidation of forest practices aimed at the stable and efficient supply of domestic timber is being promoted. Visualization of forest boundaries is important, however it takes a lot of cost and time because forest surveys are conducted by human’s exploration. This study proposes an efficient tree species identification method using deep learning method from aerial images of forests using drones for the purpose of visualizing forest boundaries. The effectiveness of the proposed method is confirmed by experiments using actual images taken by drones.
机译:作为日本的当前林业,植物森林的全规模利用期即将到来;正在促进综合森林实践,旨在稳定高效的国内木材供应。森林界限的可视化是重要的,但它需要很多成本和时间,因为森林调查是由人类的探索进行的。本研究提出了一种利用旱芳烃的空中图像从空中学习方法使用无人机来实现森林边界的目的的有效树种识别方法。通过使用无人机拍摄的实际图像来确认所提出的方法的有效性。

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