Proceedings

Find matching any: Reset
Carneiro, F.M
Cooper, J
Add filter to result:
Authors
Cammarano, D
Drexler, D
Hinsinger, P
Martre, P
Draye, X
Sessitsch, A
Pecchioni, N
Cooper, J
Helga, W
Voicu, A
Oliveira, M.F
Carneiro, F.M
Thurmond, M
del Val, M.D
Oliveira, L.P
Ortiz, B
Sanz-Saez, A
Tedesco, D
Topics
Big Data, Data Mining and Deep Learning
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2018
2022
Home » Authors » Results

Authors

Filter results2 paper(s) found.

1. Shared Protocols and Data Template in Agronomic Trials

Due to the overlap of many disciplines and the availability of novel technologies, modern agriculture has become a wide, interdisciplinary endeavor, especially in Precision Agriculture. The adoption of a standard format for reporting field experiments can help researchers to focus on the data rather than on re-formatting and understanding the structure of the data. This paper describes how a European consortium plans to: i) create a “handbook” of protocols for reporting definitions,... D. Cammarano, D. Drexler, P. Hinsinger, P. Martre, X. Draye, A. Sessitsch, N. Pecchioni, J. Cooper, W. Helga, A. Voicu

2. Predicting Below and Above Ground Peanut Biomass and Maturity Using Multi-target Regression

Peanut growth and maturity prediction can help farmers and breeding programs improving crop management. Remote sensing images collected by satellites and drones make possible and accurate crop monitoring. Today, empirical relations between crop biomass and spectral reflectance could be used for prediction of single variables such as aboveground crop biomass, pod weight (PW), or peanut maturity. Robust algorithms such as multioutput regression (MTR) implemented through multioutput random forest... M.F. Oliveira, F.M. Carneiro, M. Thurmond, M.D. Del val, L.P. Oliveira, B. Ortiz, A. Sanz-saez, D. Tedesco