Application of Deep Learning Architectures for Accurate Detection of Olive Tree Flowering Phenophase

Application of Deep Learning Architectures for Accurate Detection of Olive Tree Flowering Phenophase

The importance of monitoring and modelling the impact of climate change on crop phenology in a given ecosystem is ever-growing. For example, these procedures are useful when planning various processes that are important for plant protection. In order to proactively monitor the olive (<i>Olea e...

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Bibliographic Details
Main Authors:	Mario Milicevic, Krunoslav Zubrinic, Ivan Grbavac, Ines Obradovic
Format:	Article
Language:	English
Published:	MDPI AG 2020-07-01
Series:	Remote Sensing
Subjects:	deep learning convolutional neural networks pattern recognition data augmentation olea europaea integrated pest management
Online Access:	https://www.mdpi.com/2072-4292/12/13/2120

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