Proceedings :: International Society of Precision Agriculture

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Susin, A

Seehuber, C

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Authors

Blanke, M.M

Damerow, L.M

Seehuber, C

de Souza, M.R

Bertani, T.D

Parraga, A

Bredemeier, C

Trentin, C

Doering, D

Susin, A

Negreiros, M

Topics

Engineering Technologies and Advances

Applications of Unmanned Aerial Systems

Type

Oral

Poster

Year

2014

2018

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Filter results2 paper(s) found.
1. Precision Thinning Of Fruit Crops L. Damerow, C. Seehuber and M. Blanke University of Bonn, Germany Correspondence: damerow@uni-bonn.de Abstract for o r a l Thinning is a pre-requisite in the majority of fruit crops worldwide in order to overcome or prevent alternate bearing (change of years with large and low yields) and to provide regular yields of high quality... M.M. Blanke, L. Damerow, C. Seehuber Download paper
2. Wheat Biomass Estimation Using Visible Aerial Images and Artificial Neural Network In this study, visible RGB-based vegetation indices (VIs) from UAV high spatial resolution (1.9 cm) remote sensing images were used for modeling shoot biomass of two Brazilian wheat varieties (TBIO Toruk and BRS Parrudo). The approach consists of a combination of Artificial Neural Network (ANN) with several Vegetation Indices to model the measured crop biomass at different growth stages. Several vegetation indices were implemented: NGRDI (Normalized Green-Red Difference Index), CIVE (Color Index... M.R. De souza, T.D. Bertani, A. Parraga, C. Bredemeier, C. Trentin, D. Doering, A. Susin, M. Negreiros Download paper

Filter results2 paper(s) found.

1. Precision Thinning Of Fruit Crops

L. Damerow, C. Seehuber and M. Blanke University of Bonn, Germany Correspondence: damerow@uni-bonn.de Abstract for o r a l Thinning is a pre-requisite in the majority of fruit crops worldwide in order to overcome or prevent alternate bearing (change of years with large and low yields) and to provide regular yields of high quality... M.M. Blanke, L. Damerow, C. Seehuber

Download paper

2. Wheat Biomass Estimation Using Visible Aerial Images and Artificial Neural Network

In this study, visible RGB-based vegetation indices (VIs) from UAV high spatial resolution (1.9 cm) remote sensing images were used for modeling shoot biomass of two Brazilian wheat varieties (TBIO Toruk and BRS Parrudo). The approach consists of a combination of Artificial Neural Network (ANN) with several Vegetation Indices to model the measured crop biomass at different growth stages. Several vegetation indices were implemented: NGRDI (Normalized Green-Red Difference Index), CIVE (Color Index... M.R. De souza, T.D. Bertani, A. Parraga, C. Bredemeier, C. Trentin, D. Doering, A. Susin, M. Negreiros

Download paper