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 | 680 | 2016 |
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 | 674 | 2006 |
Neural network ensembles: evaluation of aggregation algorithms PM Granitto, PF Verdes, HA Ceccatto Artificial Intelligence 163 (2), 139-162, 2005 | 229 | 2005 |
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 | 206 | 2014 |
Weed seeds identification by machine vision PM Granitto, HD Navone, PF Verdes, HA Ceccatto Computers and Electronics in agriculture 33 (2), 91-103, 2002 | 195 | 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 | 187 | 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 | 174 | 2011 |
Seed-per-pod estimation for plant breeding using deep learning LC Uzal, GL Grinblat, R Namías, MG Larese, JS Bianchi, EN Morandi, ... Computers and electronics in agriculture 150, 196-204, 2018 | 129 | 2018 |
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 | 89 | 2007 |
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 | 76 | 2007 |
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, 761-770, 2012 | 74 | 2012 |
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 | 68 | 2010 |
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 | 64 | 2014 |
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 | 61 | 2011 |
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 | 61 | 2010 |
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 Nonlinear processes in geophysics 14 (3), 211-222, 2007 | 59 | 2007 |
Rapid and direct volatile compound profiling of black and green teas (Camellia sinensis) from different countries with PTR-ToF-MS S Yener, JA Sánchez-López, PM Granitto, L Cappellin, TD Märk, ... Talanta 152, 45-53, 2016 | 57 | 2016 |
Nonstationary time-series analysis: Accurate reconstruction of driving forces PF Verdes, PM Granitto, HD Navone, HA Ceccatto Physical Review Letters 87 (12), 124101, 2001 | 55 | 2001 |
A learning algorithm for neural network ensembles HD Navone, PM Granitto, PF Verdes, HA Ceccatto Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial …, 2001 | 52 | 2001 |
How many clusters: A validation index for arbitrary-shaped clusters AE Baya, PM Granitto IEEE/ACM Transactions on Computational Biology and Bioinformatics 10 (2 …, 2013 | 50 | 2013 |