Proceedings :: International Society of Precision Agriculture

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Favan , J.R

Filho, R.

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Authors

Favan , J.R

Faulin, G.D

Kasita Kashima, F.M

Alegre, J.

Gonçalves, L.S

da Silva, W.B

Santos, A

Costa Barboza, T

Costa, O.P

Valdes Fernandez , G

Arnosti, M.C

Silveira, G.

Filho, R.

Topics

Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture

Precision Crop Protection, Pest, and Plant Health

Type

Poster

Oral

Year

2026

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Filter results2 paper(s) found.
1. Soil Texture Classification by Image: Deep Feature Learning vs. Handcrafted Methods for Precision Agriculture Accurate soil texture classification is fundamental for precision agriculture, as it enables site-specific crop management that optimizes the utilization of agricultural resources and enhances overall crop productivity. This study presents a comparative analysis between features automatically extracted by a pre-trained SqueezeNet convolutional neural network (CNN) and three classical methods for manual feature extraction: Fast Fourier Transform (FFT), Gabor Filters, and Local Binary Patterns (LBP),... J.R. Favan , G.D. Faulin, F.M. Kasita Kashima, J. . Alegre, L.S. Gonçalves Download paper
2. Multi-Band UAV-Borne SAR Sensitivity (C, L, and P Bands) for Detecting Leaf-Cutting Ant Nests in Eucalyptus Plantations Planted forests in Brazil cover approximately 10.5 million hectares and are recognized worldwide for sustainable management and the supply of bioproducts derived from renewable raw materials. In addition, the country stands out in pulp production and exports, ranking second only to the United States. However, the planted forest sector has faced phytosanitary challenges, particularly related to leaf-cutting ants, which cause biomass losses and reduce leaf area, compromising photosynthetic capacity... W. Batista Da Silva , A. Santos, T. Costa Barboza, O.P. Costa, G. Valdes Fernandez , M. Ciscato, G. . Silveira, R. . Filho

Filter results2 paper(s) found.

1. Soil Texture Classification by Image: Deep Feature Learning vs. Handcrafted Methods for Precision Agriculture

Accurate soil texture classification is fundamental for precision agriculture, as it enables site-specific crop management that optimizes the utilization of agricultural resources and enhances overall crop productivity. This study presents a comparative analysis between features automatically extracted by a pre-trained SqueezeNet convolutional neural network (CNN) and three classical methods for manual feature extraction: Fast Fourier Transform (FFT), Gabor Filters, and Local Binary Patterns (LBP),... J.R. Favan , G.D. Faulin, F.M. Kasita Kashima, J. . Alegre, L.S. Gonçalves

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2. Multi-Band UAV-Borne SAR Sensitivity (C, L, and P Bands) for Detecting Leaf-Cutting Ant Nests in Eucalyptus Plantations

Planted forests in Brazil cover approximately 10.5 million hectares and are recognized worldwide for sustainable management and the supply of bioproducts derived from renewable raw materials. In addition, the country stands out in pulp production and exports, ranking second only to the United States. However, the planted forest sector has faced phytosanitary challenges, particularly related to leaf-cutting ants, which cause biomass losses and reduce leaf area, compromising photosynthetic capacity... W. Batista Da Silva , A. Santos, T. Costa Barboza, O.P. Costa, G. Valdes Fernandez , M. Ciscato, G. . Silveira, R. . Filho