| Image recognition with deep neural networks in presence of noise – Dealing with and taking advantage of distortions M Koziarski, B Cyganek Integrated Computer-Aided Engineering 24 (4), 337-349, 2017 | 185 | 2017 |
| Radial-based undersampling for imbalanced data classification M Koziarski Pattern Recognition 102, 107262, 2020 | 144 | 2020 |
| Radial-Based Oversampling for noisy imbalanced data classification M Koziarski, B Krawczyk, M Woźniak Neurocomputing 343, 19-33, 2019 | 133 | 2019 |
| Combined cleaning and resampling algorithm for multi-class imbalanced data with label noise M Koziarski, M Woźniak, B Krawczyk Knowledge-Based Systems 204, 106223, 2020 | 98 | 2020 |
| Radial-Based Oversampling for multiclass imbalanced data classification B Krawczyk, M Koziarski, M Woźniak IEEE Transactions on Neural Networks and Learning Systems, 2019 | 92 | 2019 |
| Impact of Low Resolution on Image Recognition with Deep Neural Networks: An Experimental Study M Koziarski, B Cyganek International Journal of Applied Mathematics and Computer Science 28 (4 …, 2018 | 86 | 2018 |
| CCR: A Combined Cleaning and Resampling Algorithm for Imbalanced Data Classification M Koziarski, M Woźniak International Journal of Applied Mathematics and Computer Science 27 (4 …, 2017 | 84 | 2017 |
| CSMOUTE: Combined synthetic oversampling and undersampling technique for imbalanced data classification M Koziarski 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 42 | 2021 |
| Radial-based approach to imbalanced data oversampling M Koziarski, B Krawczyk, M Woźniak Hybrid Artificial Intelligent Systems: 12th International Conference, HAIS …, 2017 | 25 | 2017 |
| Potential anchoring for imbalanced data classification M Koziarski Pattern recognition 120, 108114, 2021 | 23 | 2021 |
| The deterministic subspace method for constructing classifier ensembles M Koziarski, B Krawczyk, M Woźniak Pattern Analysis and Applications 20, 981-990, 2017 | 19 | 2017 |
| DiagSet: a dataset for prostate cancer histopathological image classification M Koziarski, B Cyganek, P Niedziela, B Olborski, Z Antosz, M Żydak, ... Scientific Reports 14 (1), 6780, 2024 | 18 | 2024 |
| Analysis of group evolution prediction in complex networks S Saganowski, P Bródka, M Koziarski, P Kazienko PloS one 14 (10), e0224194, 2019 | 18 | 2019 |
| Convolutional neural network-based classification of histopathological images affected by data imbalance M Koziarski, B Kwolek, B Cyganek International Conference on Pattern Recognition (ICPR), Workshop on Deep …, 2018 | 18 | 2018 |
| Multicriteria classifier ensemble learning for imbalanced data W Węgier, M Koziarski, M Woźniak IEEE Access 10, 16807-16818, 2022 | 15 | 2022 |
| RB-CCR: radial-based combined cleaning and resampling algorithm for imbalanced data classification M Koziarski, C Bellinger, M Woźniak Machine Learning 110, 3059-3093, 2021 | 13 | 2021 |
| Marine snow removal using a fully convolutional 3D neural network combined with an adaptive median filter M Koziarski, B Cyganek Pattern Recognition and Information Forensics: ICPR 2018 International …, 2019 | 13 | 2019 |
| Deep neural image denoising M Koziarski, B Cyganek International Conference on Computer Vision and Graphics, 163-173, 2016 | 13 | 2016 |
| Two-stage resampling for convolutional neural network training in the imbalanced colorectal cancer image classification M Koziarski 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 12 | 2021 |
| Breast cancer classification on histopathological images affected by data imbalance using active learning and deep convolutional neural network B Kwolek, M Koziarski, A Bukała, Z Antosz, B Olborski, P Wąsowicz, ... Artificial Neural Networks and Machine Learning–ICANN 2019: Workshop and …, 2019 | 12 | 2019 |
Boguslaw CyganekAGH University of Science and TechnologyDirección de correo verificada de agh.edu.pl
