| Semi-supervised self-training for decision tree classifiers J Tanha, M Van Someren, H Afsarmanesh International Journal of Machine Learning and Cybernetics 8, 355-370, 2017 | 251 | 2017 |
| Boosting methods for multi-class imbalanced data classification: an experimental review J Tanha, Y Abdi, N Samadi, N Razzaghi, M Asadpour Journal of Big Data 7 (1), 1-47, 2020 | 111 | 2020 |
| The role of collaborative networks in sustainability LM Camarinha-Matos, H Afsarmanesh, X Boucher Collaborative Networks for a Sustainable World: 11th IFIP WG 5.5 Working …, 2010 | 96 | 2010 |
| COVID-19 infection forecasting based on deep learning in Iran M Azarafza, M Azarafza, J Tanha MedRxiv, 2020.05. 16.20104182, 2020 | 39 | 2020 |
| Boosting for multiclass semi-supervised learning J Tanha, M Van Someren, H Afsarmanesh Pattern Recognition Letters 37, 63-77, 2014 | 29 | 2014 |
| Tune your brown clustering, please L Derczynski, S Chester, KS Bøgh International Conference Recent Advances in Natural Language Processing …, 2015 | 28 | 2015 |
| Disagreement-based co-training J Tanha, M van Someren, H Afsarmanesh 2011 IEEE 23rd international conference on tools with artificial …, 2011 | 27 | 2011 |
| Combination of ant colony optimization and Bayesian classification for feature selection in a bioinformatics dataset MH Aghdam, J Tanha, AR Naghsh-Nilchi, ME Basiri Journal of Computer Science & Systems Biology 2 (3), 186-199, 2009 | 25 | 2009 |
| An adaboost algorithm for multiclass semi-supervised learning J Tanha, M van Someren, H Afsarmanesh 2012 IEEE 12th International Conference on Data Mining, 1116-1121, 2012 | 20 | 2012 |
| Multiclass semi-supervised learning for animal behavior recognition from accelerometer data J Tanha, M Van Someren, M de Bakker, W Bouteny, ... 2012 IEEE 24th International Conference on Tools with Artificial …, 2012 | 17 | 2012 |
| A multiclass boosting algorithm to labeled and unlabeled data J Tanha International Journal of Machine Learning and Cybernetics 10 (12), 3647-3665, 2019 | 15 | 2019 |
| Relationship among prognostic indices of breast cancer using classification techniques J Tanha, H Salarabadi, M Aznab, A Farahi, M Zoberi Informatics in medicine unlocked 18, 100265, 2020 | 14 | 2020 |
| MSSBoost: A new multiclass boosting to semi-supervised learning J Tanha Neurocomputing 314, 251-266, 2018 | 14 | 2018 |
| Ensemble approaches to semi-supervised learning J Tanha SIKS, 2013 | 13 | 2013 |
| A Selection Metric for semi-supervised learning based on neighborhood construction M Emadi, J Tanha, ME Shiri, MH Aghdam Information Processing & Management 58 (2), 102444, 2021 | 9 | 2021 |
| COVID-19 detection using deep convolutional neural networks and binary differential algorithm-based feature selection from X-ray images MS Iraji, MR Feizi-Derakhshi, J Tanha Complexity 2021, 1-10, 2021 | 8 | 2021 |
| A novel semi-supervised ensemble algorithm using a performance-based selection metric to non-stationary data streams S Khezri, J Tanha, A Ahmadi, A Sharifi Neurocomputing 442, 125-145, 2021 | 8 | 2021 |
| STDS: self-training data streams for mining limited labeled data in non-stationary environment S Khezri, J Tanha, A Ahmadi, A Sharifi Applied Intelligence 50, 1448-1467, 2020 | 7 | 2020 |
| Ensemble based co-training J Tanha, M van Someren, H Afsarmanesh 23rd Benelux Conference on Artificial Intelligence, 223-231, 2011 | 7 | 2011 |
| An intelligent sample selection approach to language model adaptation for hand-written text recognition J Tanha, J de Does, K Depuydt 2014 14th International Conference on Frontiers in Handwriting Recognition …, 2014 | 5 | 2014 |
Hamideh AfsarmaneshProfessor of Computer Science, University of AmsterdamPreverjeni e-poštni naslov na uva.nl
