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Pavel Dmitriev

As seen in: Entrepreneur, MDPI, Taylor & Francis Online, ZDNet, Demand Gen Report

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Articles

Assessment of Chlorophyll Content in Maple Leaves Based on Laboratory Hyperspectral Imaging

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By Pavel Dmitriev, Boris L. Kozlovsky, Anastasiya A. Dmitrieva
| Taylor & Francis Online
ABSTRACT Chlorophyll concentrations reflect genetic, ontogenetic, phenological, and productive features of plants. For nondestructive, rapid, and large-scale determination of photosynthetic pigments, plant spectroscopy with multi- and hyperspectral sensors using vegetation indices (VIs) as proxy metrics holds great promise. One of the important problems in the spectroscopy of photosynthetic pigments is the lack of universal VIs for different plant species.
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Identifying maple species using an artificial neural network and synthetic spectral profiles on hyperspectral images of their leaves

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By Pavel Dmitriev, Alexandr Alexandrov, Artem Poltavskiy, Anastasiya A. Dmitrieva
| Taylor & Francis Online
ABSTRACT Hyperspectral plant phenotyping in combination with machine learning (ML) and deep ML algorithms has recently been used to solve a wide range of problems. One such task is the rapid and large-scale remote identification of woody plant species. This is essential for the monitoring of the condition of fruit trees, tree plantations in settlements and forest management.
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Random Reflectance: A New Hyperspectral Data Preprocessing Method for Improving the Accuracy of Machine Learning Algorithms

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By Pavel Dmitriev, Anastasiya A. Dmitrieva, Boris L. Kozlovsky
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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