| River: machine learning for streaming data in python J Montiel, M Halford, SM Mastelini, G Bolmier, R Sourty, R Vaysse, ... Journal of Machine Learning Research 22 (110), 1-8, 2021 | 292 | 2021 |
| Machine learning hyperparameter selection for contrast limited adaptive histogram equalization GFC Campos, SM Mastelini, GJ Aguiar, RG Mantovani, LF Melo, ... EURASIP Journal on Image and Video Processing 2019, 1-18, 2019 | 119 | 2019 |
| Digital image analyses as an alternative tool for chicken quality assessment DF Barbin, SM Mastelini, S Barbon Jr, GFC Campos, APAC Barbon, ... Biosystems Engineering 144, 85-93, 2016 | 91 | 2016 |
| Explainable machine learning algorithms for predicting glass transition temperatures E Alcobaça, SM Mastelini, T Botari, BA Pimentel, DR Cassar, ... Acta materialia 188, 92-100, 2020 | 90 | 2020 |
| Computer vision system and near-infrared spectroscopy for identification and classification of chicken with wooden breast, and physicochemical and technological characterization BC Geronimo, SM Mastelini, RH Carvalho, SB Júnior, DF Barbin, ... Infrared Physics & Technology 96, 303-310, 2019 | 80 | 2019 |
| Multi-target prediction of wheat flour quality parameters with near infrared spectroscopy SB Junior, SM Mastelini, APAC Barbon, DF Barbin, R Calvini, JF Lopes, ... Information processing in agriculture 7 (2), 342-354, 2020 | 57 | 2020 |
| A meta-learning approach for selecting image segmentation algorithm GJ Aguiar, RG Mantovani, SM Mastelini, AC de Carvalho, GFC Campos, ... Pattern Recognition Letters 128, 480-487, 2019 | 47 | 2019 |
| Deep regressor stacking for air ticket prices prediction E Santana, S Mastelini Simpósio Brasileiro de Sistemas de Informação (SBSI), 25-31, 2017 | 42 | 2017 |
| Predicting poultry meat characteristics using an enhanced multi-target regression method EJ Santana, BC Geronimo, SM Mastelini, RH Carvalho, DF Barbin, EI Ida, ... Biosystems Engineering 171, 193-204, 2018 | 40 | 2018 |
| Development of a flexible computer vision system for marbling classification APA da Costa Barbon, S Barbon Jr, GFC Campos, JL Seixas Jr, LM Peres, ... Computers and Electronics in Agriculture 142, 536-544, 2017 | 40 | 2017 |
| Online extra trees regressor SM Mastelini, FK Nakano, C Vens, ACP de Leon Ferreira IEEE Transactions on Neural Networks and Learning Systems 34 (10), 6755-6767, 2022 | 36 | 2022 |
| Predicting and interpreting oxide glass properties by machine learning using large datasets DR Cassar, SM Mastelini, T Botari, E Alcobaça, AC de Carvalho, ... Ceramics international 47 (17), 23958-23972, 2021 | 36 | 2021 |
| Multi-output tree chaining: An interpretative modelling and lightweight multi-target approach SM Mastelini, VGT da Costa, EJ Santana, FK Nakano, RC Guido, R Cerri, ... Journal of Signal Processing Systems 91, 191-215, 2019 | 33 | 2019 |
| DSTARS: a multi-target deep structure for tracking asynchronous regressor stacking SM Mastelini, EJ Santana, R Cerri, S Barbon Jr Applied Soft Computing 91, 106215, 2020 | 30 | 2020 |
| White striping degree assessment using computer vision system and consumer acceptance test T Kato, SM Mastelini, GFC Campos, APA da Costa Barbon, SH Prudencio, ... Asian-Australasian journal of animal sciences 32 (7), 1015, 2018 | 26* | 2018 |
| Improved prediction of soil properties with multi-target stacked generalisation on EDXRF spectra EJ Santana, FR dos Santos, SM Mastelini, FL Melquiades, S Barbon Jr Chemometrics and Intelligent Laboratory Systems 209, 104231, 2021 | 25 | 2021 |
| On ensemble techniques for data stream regression HM Gomes, J Montiel, SM Mastelini, B Pfahringer, A Bifet 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 23 | 2020 |
| Improving hierarchical classification of transposable elements using deep neural networks FK Nakano, SM Mastelini, S Barbon, R Cerri 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 22 | 2018 |
| Stacking methods for hierarchical classification F kenji Nakano, SM Mastelini, S Barbon, R Cerri 2017 16th IEEE international conference on machine learning and applications …, 2017 | 22 | 2017 |
| Machine learning unveils composition-property relationships in chalcogenide glasses SM Mastelini, DR Cassar, E Alcobaça, T Botari, AC de Carvalho, ... Acta Materialia 240, 118302, 2022 | 21 | 2022 |
Sylvio Barbon JuniorUniversity of Trieste, Department of Engineering and ArchitectureVerified email at dia.units.it
