Pablo Granitto
Pablo Granitto
CIFASIS, Rosario, Argentina
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Recursive feature elimination with random forest for PTR-MS analysis of agroindustrial products
PM Granitto, C Furlanello, F Biasioli, F Gasperi
Chemometrics and Intelligent Laboratory Systems 83 (2), 83-90, 2006
Deep learning for plant identification using vein morphological patterns
GL Grinblat, LC Uzal, MG Larese, PM Granitto
Computers and Electronics in Agriculture 127, 418-424, 2016
Neural network ensembles: evaluation of aggregation algorithms
PM Granitto, PF Verdes, HA Ceccatto
Artificial Intelligence 163 (2), 139-162, 2005
Weed seeds identification by machine vision
PM Granitto, HD Navone, PF Verdes, HA Ceccatto
Computers and Electronics in Agriculture 33 (2), 91-103, 2002
Large-scale investigation of weed seed identification by machine vision
PM Granitto, PF Verdes, HA Ceccatto
Computers and Electronics in Agriculture 47 (1), 15-24, 2005
On data analysis in PTR-TOF-MS: From raw spectra to data mining
L Cappellin, F Biasioli, PM Granitto, E Schuhfried, C Soukoulis, F Costa, ...
Sensors and Actuators B: Chemical 155 (1), 183-190, 2011
Automatic classification of legumes using leaf vein image features
MG Larese, R Namías, RM Craviotto, MR Arango, C Gallo, PM Granitto
Pattern Recognition 47 (1), 158-168, 2014
Rapid and non-destructive identification of strawberry cultivars by direct PTR-MS headspace analysis and data mining techniques
PM Granitto, F Biasioli, E Aprea, D Mott, C Furlanello, TD Märk, F Gasperi
Sensors and actuators B: Chemical 121 (2), 379-385, 2007
PTR‐TOF‐MS and data‐mining methods for rapid characterisation of agro‐industrial samples: influence of milk storage conditions on the volatile compounds profile of Trentingrana …
A Fabris, F Biasioli, PM Granitto, E Aprea, L Cappellin, E Schuhfried, ...
Journal of mass spectrometry 45 (9), 1065-1074, 2010
Modern data mining tools in descriptive sensory analysis: A case study with a Random forest approach
PM Granitto, F Gasperi, F Biasioli, E Trainotti, C Furlanello
Food Quality and Preference 18 (4), 681-689, 2007
Solving nonstationary classification problems with coupled support vector machines
GL Grinblat, LC Uzal, HA Ceccatto, PM Granitto
IEEE Transactions on Neural Networks 22 (1), 37-51, 2010
Nonstationary time-series analysis: Accurate reconstruction of driving forces
PF Verdes, PM Granitto, HD Navone, HA Ceccatto
Physical Review Letters 87 (12), 124101, 2001
PTR-ToF-MS and data mining methods: a new tool for fruit metabolomics
L Cappellin, C Soukoulis, E Aprea, P Granitto, N Dallabetta, F Costa, ...
Metabolomics 8 (5), 761-770, 2012
A learning algorithm for neural network ensembles
HD Navone, PM Granitto, PF Verdes, HA Ceccatto
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial …, 2001
Rapid characterization of dry cured ham produced following different PDOs by proton transfer reaction time of flight mass spectrometry (PTR-ToF-MS)
JS del Pulgar, C Soukoulis, F Biasioli, L Cappellin, C García, F Gasperi, ...
Talanta 85 (1), 386-393, 2011
Clustering gene expression data with a penalized graph-based metric
AE Bayá, PM Granitto
BMC bioinformatics 12 (1), 2, 2011
Prediction of minimum temperatures in an alpine region by linear and non-linear post-processing of meteorological models
E Eccel, L Ghielmi, P Granitto, R Barbiero, F Grazzini, D Cesari
Multiscale recognition of legume varieties based on leaf venation images
MG Larese, AE Bayá, RM Craviotto, MR Arango, C Gallo, PM Granitto
Expert Systems with Applications 41 (10), 4638-4647, 2014
Boosting classifiers for weed seeds identification
PM Granitto, PA Garralda, PF Verdes, HA Ceccatto
VIII Congreso Argentino de Ciencias de la Computación, 2002
Linking GC-MS and PTR-TOF-MS fingerprints of food samples
L Cappellin, E Aprea, P Granitto, R Wehrens, C Soukoulis, R Viola, ...
Chemometrics and Intelligent Laboratory Systems 118, 301-307, 2012
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