| 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 | 151 | 2017 |
| Radial-Based Oversampling for noisy imbalanced data classification M Koziarski, B Krawczyk, M Woźniak Neurocomputing 343, 19-33, 2019 | 78 | 2019 |
| Radial-based undersampling for imbalanced data classification M Koziarski Pattern Recognition 102, 107262, 2020 | 58 | 2020 |
| 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 | 53 | 2017 |
| Radial-Based Oversampling for multiclass imbalanced data classification B Krawczyk, M Koziarski, M Woźniak IEEE Transactions on Neural Networks and Learning Systems, 2019 | 49 | 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 | 43 | 2020 |
| 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 | 40 | 2018 |
| Radial-based approach to imbalanced data oversampling M Koziarski, B Krawczyk, M Woźniak International Conference on Hybrid Artificial Intelligence Systems, 318-327, 2017 | 19 | 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 | 13 | 2021 |
| 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 | 13 | 2018 |
| Analysis of group evolution prediction in complex networks S Saganowski, P Bródka, M Koziarski, P Kazienko PloS one 14 (10), e0224194, 2019 | 12 | 2019 |
| The deterministic subspace method for constructing classifier ensembles M Koziarski, B Krawczyk, M Woźniak Pattern Analysis and Applications 20 (4), 981-990, 2017 | 12 | 2017 |
| Deep neural image denoising M Koziarski, B Cyganek International Conference on Computer Vision and Graphics, 163-173, 2016 | 10 | 2016 |
| A multiresolution grid structure applied to seafloor shape modeling W Maleika, M Koziarski, P Forczmański ISPRS International Journal of Geo-Information 7 (3), 119, 2018 | 8 | 2018 |
| 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, ... International Conference on Artificial Neural Networks, 299-312, 2019 | 7 | 2019 |
| 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 | 6 | 2021 |
| Marine snow removal using a fully convolutional 3D neural network combined with an adaptive median filter M Koziarski, B Cyganek International Conference on Pattern Recognition, 16-25, 2018 | 6 | 2018 |
| Radial-based undersampling algorithm for classification of breast cancer histopathological images affected by data imbalance M Koziarski 2019 12th International Congress on Image and Signal Processing, BioMedical …, 2019 | 5 | 2019 |
| DiagSet: a dataset for prostate cancer histopathological image classification M Koziarski, B Cyganek, B Olborski, Z Antosz, M Żydak, B Kwolek, ... arXiv preprint arXiv:2105.04014, 2021 | 3 | 2021 |
| Examination of the deep neural networks in classification of distorted signals M Koziarski, B Cyganek International Conference on Artificial Intelligence and Soft Computing, 680-688, 2016 | 2 | 2016 |
Boguslaw CyganekAGH University of Science and TechnologyZweryfikowany adres z agh.edu.pl
