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https://doi.org/10.5753/sibgra...
Article . 2019 . Peer-reviewed
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Detecção de Desfolha de Soja Utilizando Redes Neurais Convolucionais

Authors: Patrik Bressan; Wesley Gonçalves;

Detecção de Desfolha de Soja Utilizando Redes Neurais Convolucionais

Abstract

The agribusiness represents a significant portion of the global economy. In Brazil, agribusiness has a significant share of the country’s economy and represented 21.6% of GDP in 2017. To increase productivity, proper management of a crop, including pest control, is of vital importance. Annually, plant pests cause losses of 20% to 40% of production. For this reason, it is important to monitor the level of defoliation to take preventive actions. Therefore, in this work an automatic methodology is proposed using Convolutional Neural Networks, to detect the level of defoliation from leaf images in the soybean crop. In addition to detecting the presence of defoliation, the proposed methodology also provides the affected regions of the leaf through the segmentation of the image. Experimental results showed 83% accuracy using the proposed methodology versus 60% of SegNet CNN. The results are promising considering that the images were captured in the field, which presents challenges such as lighting, stages of development, scale, among others.

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
bronze