Extraction of fuzzy rules from trained neural network using evolutionary algorithm. - Urszula Markowska-Kaczmar; Wojciech Trelak (ESANN, 2003)

Opening Neural Network Black Box by Evolutionary Approach. - Urszula Markowska-Kaczmar; Marcin Chumieja (HIS, 2003)

Rule Extraction from Neural Network by Genetic Algorithm with Pareto Optimization. - Urszula Markowska-Kaczmar; Pawel Wnuk-Lipinski (ICAISC, 2004)

Discovering the Mysteries of Neural Networks. - Urszula Markowska-Kaczmar; Marcin Chumieja (Int. J. Hybrid Intell. Syst., 2004)

The Influence of Parameters in Evolutionary Based Rule Extraction Method from Neural Network. - Urszula Markowska-Kaczmar (ISDA, 2005)

Support Vector Machines in Handwritten Digits Classification. - Urszula Markowska-Kaczmar; Pawel Kubacki (ISDA, 2005)

Fuzzy logic and evolutionary algorithm - two techniques in rule extraction from neural networks. - Urszula Markowska-Kaczmar; Wojciech Trelak (Neurocomputing, 2005)

Creativity of Neural Networks. - Urszula Markowska-Kaczmar; Katarzyna Czeczot (ICAISC, 2006)

Experimental Study of Evolutionary Based Method of Rule Extraction from Neural Networks in Medical Data. - Urszula Markowska-Kaczmar; Rafal Matkowski (ICDM, 2006)

IBUSCA: A Grid-based Bottom-up Subspace Clustering Algorithm. - Michal Glomba; Urszula Markowska-Kaczmar (ISDA (1), 2006)

Negative Selection based method for Multi-Class problem classification. - Urszula Markowska-Kaczmar; Bartosz Kordas (ISDA (2), 2006)

Performance Evaluation of Different Kohenen Network Parallelization Techniques. - Jan Kwiatkowski; Marcin Pawlik; Urszula Markowska-Kaczmar; Dariusz Konieczny (PARELEC, 2006)

Visualization as a method for relationship discovery in data Halina. - Halina Kwasnicka; Urszula Markowska-Kaczmar; Jacek Tomasiak (Ann. UMCS Informatica, 2006)

Mining of an electrocardiogram. - Urszula Markowska-Kaczmar; Bartosz Kordas (Ann. UMCS Informatica, 2006)

Rule extraction from a neural network by hierarchical multiobjective genetic algorithm. - Urszula Markowska-Kaczmar; Krystyna Mularczyk (Ann. UMCS Informatica, 2006)

GA-Based Pareto Optimization for Rule Extraction from Neural Networks. - Urszula Markowska-Kaczmar; Krystyna Mularczyk (Multi-Objective Machine Learning, 2006)

Semi-automatic Training Sets Acquisition for Handwriting Recognition. - Jerzy Sas; Urszula Markowska-Kaczmar (CAIP, 2007)

Semi-Supervised Handwritten Word Segmentation Using Character Samples Similarity Maximization and Evolutionary Algorithm. - Jerzy Sas; Urszula Markowska-Kaczmar (CISIM, 2007)

Extraction of Emotional Content from Music Data. - Marcin Bartoszewski; Halina Kwasnicka; Urszula Markowska-Kaczmar; Pawel B. Myszkowski (CISIM, 2008)

Learning Assistant - Personalizing Learning Paths in e-Learning Environments. - Halina Kwasnicka; Dorota Szul; Urszula Markowska-Kaczmar; Pawel B. Myszkowski (CISIM, 2008)

Data Mining Techniques in e-Learning CelGrid System. - Pawel B. Myszkowski; Halina Kwasnicka; Urszula Markowska-Kaczmar (CISIM, 2008)

Evaluation of Subspace Clustering Quality. - Urszula Markowska-Kaczmar; Arletta Hurej (HAIS, 2008)

Genetic Algorithm as a Tool for Stock Market Modelling. - Urszula Markowska-Kaczmar; Halina Kwasnicka; Marcin Szczepkowski (ICAISC, 2008)

Discovery of technical analysis patterns. - Urszula Markowska-Kaczmar; Maciej Dziedzic (IMCSIT, 2008)

Multi-class iteratively refined negative selection classifier. - Urszula Markowska-Kaczmar; Bartosz Kordas (Appl. Soft Comput., 2008)

Evolutionary Approaches to Rule Extraction from Neural Networks. - Urszula Markowska-Kaczmar (Engineering Evolutionary Intelligent Systems, 2008)

Localization of cancerous changes in images of breast tissue. - Urszula Markowska-Kaczmar; Norbert Kosmal; Piotr Orzechowski; Pawel Iwaszko; M. Baranczyk; Kazimierz Orzechowski (IMCSIT, 2009)

Kohonen's neural network and evolutionary algorithms in searching for financial investment strategy. - Urszula Markowska-Kaczmar; Krzysztof Rosól (IMCSIT, 2009)

Combined Unsupervised-Supervised Classification Method. - Urszula Markowska-Kaczmar; Tomasz Switek (KES (2), 2009)

Capillary Abnormalities Detection Using Vessel Thickness and Curvature Analysis. - Mariusz Paradowski; Urszula Markowska-Kaczmar; Halina Kwasnicka; Krzysztof Borysewicz (KES (2), 2009)

The Influence of Using Design Patterns on the Process of Implementing Genetic Algorithms. - Urszula Markowska-Kaczmar; Filip Krygowski (IEA/AIE (2), 2010)

Emotion-based Image Retrieval - an Artificial Neural Network Approach. - Katarzyna Agnieszka Olkiewicz; Urszula Markowska-Kaczmar (IMCSIT, 2010)

Biologically Inspired Agent System Based on Spiking Neural Network. - Bartlomiej Józef Dzienkowski; Urszula Markowska-Kaczmar (KES-AMSTA (2), 2010)

Intelligent Techniques in Personalization of Learning in e-Learning Systems. - Urszula Markowska-Kaczmar; Halina Kwasnicka; Mariusz Paradowski (Computational Intelligence for Technology Enhanced Learning, 2010)

Graphical Pattern Identification Inspired by Perception. - Urszula Markowska-Kaczmar; Adam Rybski (ACIIDS (2), 2011)

Towards Automatic Image Annotation Supporting Document Understanding. - Urszula Markowska-Kaczmar; Pawel Minda; Krzysztof Ociepa; Dariusz Olszowy; Roman Pawlikowski (HAIS (1), 2011)

Similar Image Recognition Inspired by Visual Cortex. - Urszula Markowska-Kaczmar; Adam Puchalski (MICAI (2), 2011)

Flocking behaviour in simple ecosystems as a result of artificial evolution. - Halina Kwasnicka; Urszula Markowska-Kaczmar; Marcin Mikosik (Appl. Soft Comput., 2011)

Plan and Goal Structure Reconstruction: An Automated and Incremental Method Based on Observation of a Single Agent. - Bartlomiej Józef Dzienkowski; Urszula Markowska-Kaczmar (CISIM, 2012)

Information Extraction from Geographical Overview Maps. - Roman Pawlikowski; Krzysztof Ociepa; Urszula Markowska-Kaczmar; Pawel B. Myszkowski (ICCCI (1), 2012)

Similarity-based training set acquisition for continuous handwriting recognition. - Jerzy Sas; Urszula Markowska-Kaczmar (Inf. Sci., 2012)

Agent Cooperation within Adversarial Teams in Dynamic Environment - Key Issues and Development Trends. - Bartlomiej Józef Dzienkowski; Urszula Markowska-Kaczmar (Trans. Comput. Collect. Intell., 2012)

Recognition of Vehicle Motion Patterns in Video Sequences. - Bartosz Buczek; Urszula Markowska-Kaczmar (ICSS, 2013)

Indoor head detection and tracking on RGBD images. - Katarzyna Nizalowska; Lukasz Burdka; Urszula Markowska-Kaczmar (FedCSIS, 2014)

Automatic information extraction from heatmaps. - Urszula Markowska-Kaczmar; Agnieszka Szymanska; Lukasz Culer (IISA, 2014)

Fast learning method of interval type-2 fuzzy neural networks. - Damian Olczyk; Urszula Markowska-Kaczmar (UKCI, 2014)

Recent Advances in Applied Computational Intelligence. - Bartosz Krawczyk; Urszula Markowska-Kaczmar; Halina Kwasnicka (Appl. Artif. Intell., 2014)

The Selected Metaheuristics Efficacy Assessment for a Given Class of Problems. - Urszula Markowska-Kaczmar; Adam Mróz (ACIIDS (1), 2015)

Logical structure recognition of diagram images. - Jerzy Sas; Urszula Markowska-Kaczmar (FedCSIS, 2015)

A Language-Independent Method for Detection and Correction of Alignment Errors in Parallel Corpora. - Katarzyna Nizalowska; Urszula Markowska-Kaczmar (NLDB, 2015)

Automatic Indication of Heat Loss in Thermograms of Buildings. - Urszula Markowska-Kaczmar; Agnieszka Szymanska; Lukasz Culer (Int. J. Comput. Sci. Appl., 2015)

Image-based logical document structure recognition. - Grzegorz Kamola; Michal Spytkowski; Mariusz Paradowski; Urszula Markowska-Kaczmar (Pattern Anal. Appl., 2015)

Spiking neural network vs multilayer perceptron: who is the winner in the racing car computer game. - Urszula Markowska-Kaczmar; Mateusz Koldowski (Soft Comput., 2015)

A* Heuristic Based on a Hierarchical Space Model Extracted from Game Replays. - Bartlomiej Józef Dzienkowski; Urszula Markowska-Kaczmar (FedCSIS, 2016)

Employing Game Theory and Computational Intelligence to Find the Optimal Strategy of an Autonomous Underwater Vehicle against a Submarine. - Bartlomiej Józef Dzienkowski; Christopher Strode; Urszula Markowska-Kaczmar (FedCSIS, 2016)

Caption-guided patent image segmentation. - Urszula Markowska-Kaczmar; Jerzy Sas; Anastasia Moumtzidou (FedCSIS, 2016)

American Sign Language Fingerspelling Recognition Using Wide Residual Networks. - Kacper Kania; Urszula Markowska-Kaczmar (ICAISC (1), 2018)

Is Convolutional Network Competitive for Vision Method in the Furniture Dowel Quality Control? - Urszula Markowska-Kaczmar; Michal Skiba (INISTA, 2018)

Inference Ability Assessment of Modified Differential Neural Computer. - Urszula Markowska-Kaczmar; Grzegorz Kulakowski (ACIIDS (1), 2020)

Markov network versus recurrent neural network in forming herd behavior based on sight and simple sound communication. - Urszula Markowska-Kaczmar; Tomasz Marcinkowski (Appl. Soft Comput., 2020)

Comparison of Attention-based Deep Learning Models for EEG Classification. - Giulia Cisotto; Alessio Zanga; Joanna Chlebus; Italo Zoppis; Sara Manzoni; Urszula Markowska-Kaczmar (CoRR, 2020)

Capsule Network Versus Convolutional Neural Network in Image Classification - Comparative Analysis. - Ewa Juralewicz; Urszula Markowska-Kaczmar (ICCS (5), 2021)

Interpreting Neural Networks Prediction for a Single Instance via Random Forest Feature Contributions. - Anna Palczewska; Urszula Markowska-Kaczmar (ICCS (2), 2021)

Creating herd behavior by virtual agents using neural networks. - Urszula Markowska-Kaczmar; Adrian Slimak (KES, 2021)

Utterance Style Transfer Using Deep Models. - Daniel Popek; Urszula Markowska-Kaczmar (KES, 2021)

3D robotic navigation using a vision-based deep reinforcement learning model. - Piotr Zielinski; Urszula Markowska-Kaczmar (Appl. Soft Comput., 2021)

Human flow recognition using deep networks and vision methods. - Mateusz Zimoch; Urszula Markowska-Kaczmar (Eng. Appl. Artif. Intell., 2021)

Extreme learning machine versus classical feedforward network. - Urszula Markowska-Kaczmar; Michal Kosturek (Neural Comput. Appl., 2021)

Gradient Overdrive: Avoiding Negative Randomness Effects in Stochastic Gradient Descent. - Filip Strzalka; Urszula Markowska-Kaczmar (ACIIDS (Companion 1), 2024)

Deep learning for cancer cell detection: do we need dedicated models? - Michal Karol; Martin Tabakov; Urszula Markowska-Kaczmar; Lukasz Fulawka (Artif. Intell. Rev., 2024)

Masticatory organ dysfunction recognition based on multimodal information. - Urszula Markowska-Kaczmar; Michal Karolewski; Michal Wawrzyniak; Karol Szymonczyk; Joanna Szolomicka; Jakub Pyka; Karol Kulawiec; Aneta Demidas (Eng. Appl. Artif. Intell., 2025)