Deep convolutional neural networks as a decision support tool in medical problems - malignant melanoma case study. - Arkadiusz Kwasigroch; Agnieszka Mikolajczyk; Michal Grochowski (KKA, 2017)

Intelligent system supporting diagnosis of malignant melanoma. - Agnieszka Mikolajczyk; Arkadiusz Kwasigroch; Michal Grochowski (KKA, 2017)

Deep neural networks approach to skin lesions classification - A comparative analysis. - Arkadiusz Kwasigroch; Agnieszka Mikolajczyk; Michal Grochowski (MMAR, 2017)

Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study. - Agnieszka Mikolajczyk; Michal Grochowski; Arkadiusz Kwasigroch (MMAR, 2018)

Style transfer-based image synthesis as an efficient regularization technique in deep learning. - Agnieszka Mikolajczyk; Michal Grochowski (MMAR, 2019)

Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks. - Zuzanna Klawikowska; Agnieszka Mikolajczyk; Michal Grochowski (ICAISC (1), 2020)

Neural Architecture Search for Skin Lesion Classification. - Arkadiusz Kwasigroch; Michal Grochowski; Agnieszka Mikolajczyk (IEEE Access, 2020)

Global explanations for discovering bias in data. - Agnieszka Mikolajczyk; Michal Grochowski; Arkadiusz Kwasigroch (CoRR, 2020)

Joint Prediction of Truecasing and Punctuation for Conversational Speech in Low-Resource Scenarios. - Raghavendra Pappagari; Piotr Zelasko; Agnieszka Mikolajczyk; Piotr Pezik; Najim Dehak (ASRU, 2021)

Waste detection in Pomerania: non-profit project for detecting waste in environment. - Sylwia Majchrowska; Agnieszka Mikolajczyk; Maria Ferlin; Zuzanna Klawikowska; Marta A. Plantykow; Arkadiusz Kwasigroch; Karol Majek (CoRR, 2021)

Towards Explainable Classifiers Using the Counterfactual Approach - Global Explanations for Discovering Bias in Data. - Agnieszka Mikolajczyk; Michal Grochowski; Arkadiusz Kwasigroch (J. Artif. Intell. Soft Comput. Res., 2021)

Keyword Extraction from Short Texts with a Text-to-Text Transfer Transformer. - Piotr Pezik; Agnieszka Mikolajczyk; Adam Wawrzynski; Bartlomiej Niton; Maciej Ogrodniczuk (ACIIDS (Companion), 2022)

The (de)biasing Effect of GAN-Based Augmentation Methods on Skin Lesion Images. - Agnieszka Mikolajczyk; Sylwia Majchrowska; Sandra Carrasco Limeros (MICCAI (8), 2022)

PolEval 2022/23 Challenge Tasks and Results. - Lukasz Kobylinski; Maciej Ogrodniczuk; Piotr Rybak; Piotr Przybyla; Piotr Pezik; Agnieszka Mikolajczyk; Wojciech Janowski; Michal Marcinczuk; Aleksander Smywinski-Pohl (FedCSIS, 2023)

Transferable Keyword Extraction and Generation with Text-to-Text Language Models. - Piotr Pezik; Agnieszka Mikolajczyk; Adam Wawrzynski; Filip Zarnecki; Bartlomiej Niton; Maciej Ogrodniczuk (ICCS (2), 2023)

On the Importance of Sign Labeling: The Hamburg Sign Language Notation System Case Study. - Maria Ferlin; Sylwia Majchrowska; Marta A. Plantykow; Alicja Kwasniwska; Agnieszka Mikolajczyk-Barela; Milena Olech; Jakub Nalepa (CoRR, 2023)

Data augmentation and explainability for bias discovery and mitigation in deep learning. - Agnieszka Mikolajczyk-Barela (CoRR, 2023)

A survey on bias in machine learning research. - Agnieszka Mikolajczyk-Barela; Michal Grochowski (CoRR, 2023)

Targeted Data Augmentation for bias mitigation. - Agnieszka Mikolajczyk-Barela; Maria Ferlin; Michal Grochowski (CoRR, 2023)

Quantifying inconsistencies in the Hamburg Sign Language Notation System. - Maria Ferlin; Sylwia Majchrowska; Marta A. Plantykow; Alicja Kwasniewska; Agnieszka Mikolajczyk-Barela; Milena Olech; Jakub Nalepa (Expert Syst. Appl., 2024)

Targeted data augmentation for improving model robustness. - Agnieszka Mikolajczyk-Barela; Maria Ferlin; Michal Grochowski (Int. J. Appl. Math. Comput. Sci., 2025)