| Evaluating and Comparing Classifiers: Review, Some Recommendations and Limitations K Stąpor International Conference on Computer Recognition Systems, 12-21, 2017 | 70 | 2017 |
| Segmentation of fundus eye images using methods of mathematical morphology for glaucoma diagnosis K Stapor, A Świtonski, R Chrastek, G Michelson International Conference on Computational Science, 41-48, 2004 | 69 | 2004 |
| Validation of Emotiv EPOC+ for extracting ERP correlates of emotional face processing K Kotowski, K Stapor, J Leski, M Kotas Biocybernetics and Biomedical Engineering 38 (4), 773-781, 2018 | 40 | 2018 |
| Automatyczna klasyfikacja obiektów K Stąpor Akademicka Oficyna Wydawnicza EXIT, 2005 | 34 | 2005 |
| Weighted k-nearest-neighbor techniques for high throughput screening data K Kozak, M Kozak, K Stapor Int. J. Biomed. Sci 1, 155-160, 2006 | 29 | 2006 |
| Metody klasyfikacji obiektów w wizji komputerowej K Stąpor Wydawnictwo Naukowe PWN, 2011 | 26 | 2011 |
| Using the one–versus–rest strategy with samples balancing to improve pairwise coupling classification W Chmielnicki, K Stąpor International Journal of Applied Mathematics and Computer Science 26 (1 …, 2016 | 16 | 2016 |
| Model-based recognition of polyhedral objects from single intensity image using aspect graph K Stąpor, K Skabek, A Tomaka Machine Graphics and Vision 2, 1999 | 15 | 1999 |
| Protein fold recognition with combined SVM-RDA classifier W Chmielnicki, K Sta̧por International Conference on Hybrid Artificial Intelligence Systems, 162-169, 2010 | 14 | 2010 |
| Geohraphic map image interpretation: survey and problems K Stąpor Machine Graphics and Vision 9 (1/2), 497-518, 2000 | 12 | 2000 |
| An efficient multi-class support vector machine classifier for protein fold recognition W Chmielnicki, K Stapor, I Roterman-Konieczna Advances in Bioinformatics, 77-84, 2010 | 10 | 2010 |
| Chaperonin Structure-The Large Multi-Subunit Protein Complex M Banach, K Stąpor, I Roterman International journal of molecular sciences 10 (3), 844-861, 2009 | 10 | 2009 |
| Investigation of normalization techniques and their impact on a recognition rate in handwritten numeral recognition W Chmielnicki, K Stapor Schedae Informaticae 19, 53-78, 2015 | 9* | 2015 |
| An improved protein fold recognition with support vector machines W Chmielnicki, I Roterman‐Konieczna, K Stąpor Expert Systems 29 (2), 200-211, 2012 | 9 | 2012 |
| Automatic analysis of fundus eye images using mathematical morphology and neural networks for supporting glaucoma diagnosis K Stąpor, A Świtoński Machine Graphics and Vision 13 (1/2), 65-78, 2004 | 9 | 2004 |
| Statistical dictionaries for hypothetical in silico model of the early-stage intermediate in protein folding B Kalinowska, P Fabian, K Stąpor, I Roterman Journal of computer-aided molecular design 29 (7), 609-618, 2015 | 8 | 2015 |
| CASE dla ludzi P Fuglewicz, K Stąpor, A Trojnar Wydaw. Lupus, 1995 | 8 | 1995 |
| Machine Learning Methods for the Protein Fold Recognition Problem K Stapor, I Roterman-Konieczna, P Fabian Machine Learning Paradigms, 101-127, 2019 | 7 | 2019 |
| Mean Shift Segmentation, Genetic Algorithms and Support Vector Machines for Identification of Glaucoma in Fundus Eye Images K Stapor, A Brueckner Computer Recognition Systems, 679-685, 2005 | 7 | 2005 |
| A vectorized thinning algorithm for handwritten symbols recognition K Stąpor Machine Graphics and Vision 8 (3), 341-352, 1999 | 7 | 1999 |
