| Lyapunov exponent of EEG signal for epileptic seizure characterization B Swiderski, S Osowski, A Rysz Proceedings of the 2005 European Conference on Circuit Theory and Design …, 2005 | 57 | 2005 |
| Multistage classification by using logistic regression and neural networks for assessment of financial condition of company B Swiderski, J Kurek, S Osowski Decision Support Systems 52 (2), 539-547, 2012 | 50 | 2012 |
| Melanoma recognition using extended set of descriptors and classifiers M Kruk, B Świderski, S Osowski, J Kurek, M Słowińska, I Walecka EURASIP journal on Image and Video Processing 2015, 1-10, 2015 | 49 | 2015 |
| Deep learning and non-negative matrix factorization in recognition of mammograms B Swiderski, J Kurek, S Osowski, M Kruk, W Barhoumi Eighth International Conference on Graphic and Image Processing (ICGIP 2016 …, 2017 | 44 | 2017 |
| Epileptic seizure characterization by Lyapunov exponent of EEG signal S Osowski, B Swiderski, A Cichocki, A Rysz COMPEL-The international journal for computation and mathematics in …, 2007 | 41 | 2007 |
| Novel methods of image description and ensemble of classifiers in application to mammogram analysis B Swiderski, S Osowski, J Kurek, M Kruk, I Lugowska, P Rutkowski, ... Expert Systems with Applications 81, 67-78, 2017 | 35 | 2017 |
| False-positive reduction in computer-aided mass detection using mammographic texture analysis and classification S Dhahbi, W Barhoumi, J Kurek, B Swiderski, M Kruk, E Zagrouba Computer methods and programs in biomedicine 160, 75-83, 2018 | 30 | 2018 |
| Deep learning versus classical neural approach to mammogram recognition J Kurek, B Świderski, S Osowski, M Kruk, W Barhoumi Bulletin of the Polish Academy of Sciences. Technical Sciences 66 (6), 831-840, 2018 | 27 | 2018 |
| Single-class SVM and directed transfer function approach to the localization of the region containing epileptic focus B Swiderski, S Osowski, A Cichocki, A Rysz Neurocomputing 72 (7-9), 1575-1583, 2009 | 27 | 2009 |
| Deep neural system for supporting tumor recognition of mammograms using modified GAN B Swiderski, L Gielata, P Olszewski, S Osowski, M Kołodziej Expert Systems with Applications 164, 113968, 2021 | 26 | 2021 |
| Ensemble of classifiers and wavelet transformation for improved recognition of Fuhrman grading in clear-cell renal carcinoma M Kruk, J Kurek, S Osowski, R Koktysz, B Swiderski, T Markiewicz Biocybernetics and Biomedical Engineering 37 (3), 357-364, 2017 | 26 | 2017 |
| Deep learning in assessment of drill condition on the basis of images of drilled holes J Kurek, B Swiderski, A Jegorowa, M Kruk, S Osowski Eighth International Conference on Graphic and Image Processing (ICGIP 2016 …, 2017 | 25 | 2017 |
| Epileptic seizure prediction using Lyapunov exponents and support vector machine B Świderski, S Osowski, A Cichocki, A Rysz Adaptive and Natural Computing Algorithms: 8th International Conference …, 2007 | 18 | 2007 |
| Texture characterization based on the Kolmogorov–Smirnov distance B Swiderski, S Osowski, M Kruk, J Kurek Expert systems with applications 42 (1), 503-509, 2015 | 17 | 2015 |
| Random CNN structure: tool to increase generalization ability in deep learning B Swiderski, S Osowski, G Gwardys, J Kurek, M Slowinska, I Lugowska Eurasip journal on image and video processing 2022 (1), 3, 2022 | 13 | 2022 |
| Data augmentation techniques for transfer learning improvement in drill wear classification using convolutional neural network J Kurek, I Antoniuk, J Górski, A Jegorowa, B Świderski, M Kruk, ... Machine Graphics and Vision 28, 2019 | 13 | 2019 |
| Aggregation of classifiers ensemble using local discriminatory power and quantiles B Swiderski, S Osowski, M Kruk, W Barhoumi Expert Systems with Applications 46, 316-323, 2016 | 13 | 2016 |
| Application of siamese networks to the recognition of the drill wear state based on images of drilled holes J Kurek, I Antoniuk, B Świderski, A Jegorowa, M Bukowski Sensors 20 (23), 6978, 2020 | 12 | 2020 |
| Classifiers ensemble of transfer learning for improved drill wear classification using convolutional neural network J Kurek, I Antoniuk, J Górski, A Jegorowa, B Świderski, M Kruk, ... Machine Graphics & Vision 28 (1/4), 2019 | 12 | 2019 |
| Prediction of Blueberry (Vaccinium corymbosum L.) Yield Based on Artificial Intelligence Methods G Niedbała, J Kurek, B Świderski, T Wojciechowski, I Antoniuk, K Bobran Agriculture 12 (12), 2089, 2022 | 11 | 2022 |
Michał KruksggwGeverifieerd e-mailadres voor iem.pw.edu.pl
