Proceedings :: International Society of Precision Agriculture

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Ochoa, O

Beserra, D.V

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Authors

Erazo, E

Mosquera, C

Ochoa, O

Costa G. da Silva, Y

Freitas, E

Costa, P.S

Beserra, D.V

Gomes, D.G

Topics

Artificial Intelligence (AI) in Agriculture

Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture

Type

Oral

Poster

Year

2024

2026

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Filter results2 paper(s) found.
1. RMAPs: an Integrated Tool to Delimitate Homogeneous Management Zones Management zones are one of the most studied methods in precision agriculture to optimize crop yield from the soil, plant, management, and climate input parameters. We present Rmaps, an R package that integrates soil and crop yield spatial variability using geostatistical methods and one-hidden-layer perceptron (OHLP) to identify how input parameters influence crop yield and delimitate homogenous zones. From georeferenced data of soil, plant, management, climate, and crop yield parameters, Rmaps... E. Erazo, C. Mosquera, O. Ochoa Download paper
2. Detection of Banana Bunches and Peduncles in the Prata Catarina Cultivar Using Faster R-CNN With Transfer Learning Banana is one of the most produced and consumed fruits worldwide, being strategic for precision agriculture, especially in applications aimed at intelligent management and automated harvesting. Its economic and social relevance in tropical countries reinforces the need for technological solutions that increase productive efficiency and reduce losses in the field. In this context, the automatic detection of bunches and stalks in a natural environment represents a relevant challenge due to occlusion,... Y. Costa G. Da Silva, E. Freitas, P.S. Costa, D.V. Beserra, D.G. Gomes Download paper

Filter results2 paper(s) found.

1. RMAPs: an Integrated Tool to Delimitate Homogeneous Management Zones

Management zones are one of the most studied methods in precision agriculture to optimize crop yield from the soil, plant, management, and climate input parameters. We present Rmaps, an R package that integrates soil and crop yield spatial variability using geostatistical methods and one-hidden-layer perceptron (OHLP) to identify how input parameters influence crop yield and delimitate homogenous zones. From georeferenced data of soil, plant, management, climate, and crop yield parameters, Rmaps... E. Erazo, C. Mosquera, O. Ochoa

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2. Detection of Banana Bunches and Peduncles in the Prata Catarina Cultivar Using Faster R-CNN With Transfer Learning

Banana is one of the most produced and consumed fruits worldwide, being strategic for precision agriculture, especially in applications aimed at intelligent management and automated harvesting. Its economic and social relevance in tropical countries reinforces the need for technological solutions that increase productive efficiency and reduce losses in the field. In this context, the automatic detection of bunches and stalks in a natural environment represents a relevant challenge due to occlusion,... Y. Costa G. Da Silva, E. Freitas, P.S. Costa, D.V. Beserra, D.G. Gomes

Download paper