Early detection of Phytophthora infestans in potato plants using hyperspectral imaging, local comparison and a convolutional neural network
Author:
Publisher
Elsevier BV
Subject
Artificial Intelligence,General Agricultural and Biological Sciences,Computer Science (miscellaneous)
Reference13 articles.
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2. Potato late blight detection at the leaf and canopy level using hyperspectral data;Fernández;Can. J. Remote Sens.,2020
3. Hyperspectral measurements enable pre-symptomatic detection and differentiation of contrasting physiological effects of late blight and early blight in potato;Gold;Remote Sens.,2020
4. Double setting of potato seed tubers as a new approach to research primary stem blight (phytophthora infestans (mont.) de bary);Keil;Am. J. Potato Res.,2010
5. Detection of latent potato late blight by hyperspectral imaging;Kool,2021
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1. The Application of Deep Learning in the Whole Potato Production Chain: A Comprehensive Review;Agriculture;2024-07-25
2. A machine learning algorithm for the automatic classification of Phytophthora infestans genotypes into clonal lineages;Applications in Plant Sciences;2024-07-23
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