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Drones, Volume 6, Issue 1

2022 January - 27 articles

Cover Story: Recent technological developments in the primary sector and machine learning algorithms allow the combined application of many promising solutions in precision agriculture. The advent of datasets from different perspectives offers multiple benefits, such as a spheric view of objects and inference results from the detection of multiple objects per image. However, it also creates crucial obstacles, such as total identifications (ground truths) and processing concerns that can lead to devastating consequences, including false-positive detections with other erroneous conclusions or even the inability to extract results. This paper introduces the machine learning algorithm (Yolov5) on a novel dataset based on perennial fruit crops, such as sweet cherries, to enhance precision agriculture resiliency against stress/disease (Armillaria). View this paper
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Drones - ISSN 2504-446X
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