Urszula Markowska-Kaczmar

71 papers A* 1B 3C 11Misc 4Journal 20Unranked 29

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Masticatory organ dysfunction recognition based on multimodal information. Eng. Appl. Artif. Intell. Urszula Markowska-Kaczmar, Michal Karolewski, Michal Wawrzyniak, Karol Szymonczyk, Joanna Szolomicka, Jakub Pyka, Karol Kulawiec, Aneta Demidas
2024	J	`jnl`	Deep learning for cancer cell detection: do we need dedicated models? Artif. Intell. Rev. Michal Karol, Martin Tabakov, Urszula Markowska-Kaczmar, Lukasz Fulawka
2024	—	`conf`	Gradient Overdrive: Avoiding Negative Randomness Effects in Stochastic Gradient Descent. ACIIDS (Companion 1) Filip Strzalka, Urszula Markowska-Kaczmar
2021	J	`jnl`	3D robotic navigation using a vision-based deep reinforcement learning model. Appl. Soft Comput. Piotr Zielinski, Urszula Markowska-Kaczmar
2021	—	`conf`	Capsule Network Versus Convolutional Neural Network in Image Classification - Comparative Analysis. ICCS (5) Ewa Juralewicz, Urszula Markowska-Kaczmar
2021	B	`conf`	Creating herd behavior by virtual agents using neural networks. KES Urszula Markowska-Kaczmar, Adrian Slimak
2021	J	`jnl`	Extreme learning machine versus classical feedforward network. Neural Comput. Appl. Urszula Markowska-Kaczmar, Michal Kosturek
2021	J	`jnl`	Human flow recognition using deep networks and vision methods. Eng. Appl. Artif. Intell. Mateusz Zimoch, Urszula Markowska-Kaczmar
2021	—	`conf`	Interpreting Neural Networks Prediction for a Single Instance via Random Forest Feature Contributions. ICCS (2) Anna Palczewska, Urszula Markowska-Kaczmar
2021	B	`conf`	Utterance Style Transfer Using Deep Models. KES Daniel Popek, Urszula Markowska-Kaczmar
2020	J	`jnl`	Comparison of Attention-based Deep Learning Models for EEG Classification. CoRR Giulia Cisotto, Alessio Zanga, Joanna Chlebus, Italo Zoppis, Sara Manzoni, Urszula Markowska-Kaczmar
2020	—	`conf`	Inference Ability Assessment of Modified Differential Neural Computer. ACIIDS (1) Urszula Markowska-Kaczmar, Grzegorz Kulakowski
2020	J	`jnl`	Markov network versus recurrent neural network in forming herd behavior based on sight and simple sound communication. Appl. Soft Comput. Urszula Markowska-Kaczmar, Tomasz Marcinkowski
2018	—	`conf`	American Sign Language Fingerspelling Recognition Using Wide Residual Networks. ICAISC (1) Kacper Kania, Urszula Markowska-Kaczmar
2018	C	`conf`	Is Convolutional Network Competitive for Vision Method in the Furniture Dowel Quality Control? INISTA Urszula Markowska-Kaczmar, Michal Skiba
2016	C	`conf`	A* Heuristic Based on a Hierarchical Space Model Extracted from Game Replays. FedCSIS Bartlomiej Józef Dzienkowski, Urszula Markowska-Kaczmar
2016	C	`conf`	Caption-guided patent image segmentation. FedCSIS Urszula Markowska-Kaczmar, Jerzy Sas, Anastasia Moumtzidou
2016	C	`conf`	Employing Game Theory and Computational Intelligence to Find the Optimal Strategy of an Autonomous Underwater Vehicle against a Submarine. FedCSIS Bartlomiej Józef Dzienkowski, Christopher Strode, Urszula Markowska-Kaczmar
2015	C	`conf`	A Language-Independent Method for Detection and Correction of Alignment Errors in Parallel Corpora. NLDB Katarzyna Nizalowska, Urszula Markowska-Kaczmar
2015	J	`jnl`	Automatic Indication of Heat Loss in Thermograms of Buildings. Int. J. Comput. Sci. Appl. Urszula Markowska-Kaczmar, Agnieszka Szymanska, Lukasz Culer
2015	J	`jnl`	Image-based logical document structure recognition. Pattern Anal. Appl. Grzegorz Kamola, Michal Spytkowski, Mariusz Paradowski, Urszula Markowska-Kaczmar
2015	C	`conf`	Logical structure recognition of diagram images. FedCSIS Jerzy Sas, Urszula Markowska-Kaczmar
2015	J	`jnl`	Spiking neural network vs multilayer perceptron: who is the winner in the racing car computer game. Soft Comput. Urszula Markowska-Kaczmar, Mateusz Koldowski
2015	—	`conf`	The Selected Metaheuristics Efficacy Assessment for a Given Class of Problems. ACIIDS (1) Urszula Markowska-Kaczmar, Adam Mróz
2014	—	`conf`	Automatic information extraction from heatmaps. IISA Urszula Markowska-Kaczmar, Agnieszka Szymanska, Lukasz Culer
2014	—	`conf`	Fast learning method of interval type-2 fuzzy neural networks. UKCI Damian Olczyk, Urszula Markowska-Kaczmar
2014	C	`conf`	Indoor head detection and tracking on RGBD images. FedCSIS Katarzyna Nizalowska, Lukasz Burdka, Urszula Markowska-Kaczmar
2014	J	`jnl`	Recent Advances in Applied Computational Intelligence. Appl. Artif. Intell. Bartosz Krawczyk, Urszula Markowska-Kaczmar, Halina Kwasnicka
2013	—	`conf`	Recognition of Vehicle Motion Patterns in Video Sequences. ICSS Bartosz Buczek, Urszula Markowska-Kaczmar
2012	J	`jnl`	Agent Cooperation within Adversarial Teams in Dynamic Environment - Key Issues and Development Trends. Trans. Comput. Collect. Intell. Bartlomiej Józef Dzienkowski, Urszula Markowska-Kaczmar
2012	—	`conf`	Information Extraction from Geographical Overview Maps. ICCCI (1) Roman Pawlikowski, Krzysztof Ociepa, Urszula Markowska-Kaczmar, Pawel B. Myszkowski
2012	—	`conf`	Plan and Goal Structure Reconstruction: An Automated and Incremental Method Based on Observation of a Single Agent. CISIM Bartlomiej Józef Dzienkowski, Urszula Markowska-Kaczmar
2012	J	`jnl`	Similarity-based training set acquisition for continuous handwriting recognition. Inf. Sci. Jerzy Sas, Urszula Markowska-Kaczmar
2011	J	`jnl`	Flocking behaviour in simple ecosystems as a result of artificial evolution. Appl. Soft Comput. Halina Kwasnicka, Urszula Markowska-Kaczmar, Marcin Mikosik
2011	—	`conf`	Graphical Pattern Identification Inspired by Perception. ACIIDS (2) Urszula Markowska-Kaczmar, Adam Rybski
2011	—	`conf`	Similar Image Recognition Inspired by Visual Cortex. MICAI (2) Urszula Markowska-Kaczmar, Adam Puchalski
2011	—	`conf`	Towards Automatic Image Annotation Supporting Document Understanding. HAIS (1) Urszula Markowska-Kaczmar, Pawel Minda, Krzysztof Ociepa, Dariusz Olszowy, Roman Pawlikowski
2010	—	`conf`	Biologically Inspired Agent System Based on Spiking Neural Network. KES-AMSTA (2) Bartlomiej Józef Dzienkowski, Urszula Markowska-Kaczmar
2010	—	`conf`	Emotion-based Image Retrieval - an Artificial Neural Network Approach. IMCSIT Katarzyna Agnieszka Olkiewicz, Urszula Markowska-Kaczmar
2010	—	`ch.`	Intelligent Techniques in Personalization of Learning in e-Learning Systems. Computational Intelligence for Technology Enhanced Learning Urszula Markowska-Kaczmar, Halina Kwasnicka, Mariusz Paradowski
2010	—	`conf`	The Influence of Using Design Patterns on the Process of Implementing Genetic Algorithms. IEA/AIE (2) Urszula Markowska-Kaczmar, Filip Krygowski
2009	—	`conf`	Capillary Abnormalities Detection Using Vessel Thickness and Curvature Analysis. KES (2) Mariusz Paradowski, Urszula Markowska-Kaczmar, Halina Kwasnicka, Krzysztof Borysewicz
2009	—	`conf`	Combined Unsupervised-Supervised Classification Method. KES (2) Urszula Markowska-Kaczmar, Tomasz Switek
2009	—	`conf`	Kohonen's neural network and evolutionary algorithms in searching for financial investment strategy. IMCSIT Urszula Markowska-Kaczmar, Krzysztof Rosól
2009	—	`conf`	Localization of cancerous changes in images of breast tissue. IMCSIT Urszula Markowska-Kaczmar, Norbert Kosmal, Piotr Orzechowski, Pawel Iwaszko, M. Baranczyk, Kazimierz Orzechowski
2008	—	`conf`	Data Mining Techniques in e-Learning CelGrid System. CISIM Pawel B. Myszkowski, Halina Kwasnicka, Urszula Markowska-Kaczmar
2008	—	`conf`	Discovery of technical analysis patterns. IMCSIT Urszula Markowska-Kaczmar, Maciej Dziedzic
2008	Misc	`conf`	Evaluation of Subspace Clustering Quality. HAIS Urszula Markowska-Kaczmar, Arletta Hurej
2008	—	`ch.`	Evolutionary Approaches to Rule Extraction from Neural Networks. Engineering Evolutionary Intelligent Systems Urszula Markowska-Kaczmar
2008	—	`conf`	Extraction of Emotional Content from Music Data. CISIM Marcin Bartoszewski, Halina Kwasnicka, Urszula Markowska-Kaczmar, Pawel B. Myszkowski
2008	Misc	`conf`	Genetic Algorithm as a Tool for Stock Market Modelling. ICAISC Urszula Markowska-Kaczmar, Halina Kwasnicka, Marcin Szczepkowski
2008	—	`conf`	Learning Assistant - Personalizing Learning Paths in e-Learning Environments. CISIM Halina Kwasnicka, Dorota Szul, Urszula Markowska-Kaczmar, Pawel B. Myszkowski
2008	J	`jnl`	Multi-class iteratively refined negative selection classifier. Appl. Soft Comput. Urszula Markowska-Kaczmar, Bartosz Kordas
2007	—	`conf`	Semi-Supervised Handwritten Word Segmentation Using Character Samples Similarity Maximization and Evolutionary Algorithm. CISIM Jerzy Sas, Urszula Markowska-Kaczmar
2007	C	`conf`	Semi-automatic Training Sets Acquisition for Handwriting Recognition. CAIP Jerzy Sas, Urszula Markowska-Kaczmar
2006	Misc	`conf`	Creativity of Neural Networks. ICAISC Urszula Markowska-Kaczmar, Katarzyna Czeczot
2006	A*	`conf`	Experimental Study of Evolutionary Based Method of Rule Extraction from Neural Networks in Medical Data. ICDM Urszula Markowska-Kaczmar, Rafal Matkowski
2006	—	`ch.`	GA-Based Pareto Optimization for Rule Extraction from Neural Networks. Multi-Objective Machine Learning Urszula Markowska-Kaczmar, Krystyna Mularczyk
2006	—	`conf`	IBUSCA: A Grid-based Bottom-up Subspace Clustering Algorithm. ISDA (1) Michal Glomba, Urszula Markowska-Kaczmar
2006	J	`jnl`	Mining of an electrocardiogram. Ann. UMCS Informatica Urszula Markowska-Kaczmar, Bartosz Kordas
2006	—	`conf`	Negative Selection based method for Multi-Class problem classification. ISDA (2) Urszula Markowska-Kaczmar, Bartosz Kordas
2006	—	`conf`	Performance Evaluation of Different Kohenen Network Parallelization Techniques. PARELEC Jan Kwiatkowski, Marcin Pawlik, Urszula Markowska-Kaczmar, Dariusz Konieczny
2006	J	`jnl`	Rule extraction from a neural network by hierarchical multiobjective genetic algorithm. Ann. UMCS Informatica Urszula Markowska-Kaczmar, Krystyna Mularczyk
2006	J	`jnl`	Visualization as a method for relationship discovery in data Halina. Ann. UMCS Informatica Halina Kwasnicka, Urszula Markowska-Kaczmar, Jacek Tomasiak
2005	J	`jnl`	Fuzzy logic and evolutionary algorithm - two techniques in rule extraction from neural networks. Neurocomputing Urszula Markowska-Kaczmar, Wojciech Trelak
2005	C	`conf`	Support Vector Machines in Handwritten Digits Classification. ISDA Urszula Markowska-Kaczmar, Pawel Kubacki
2005	C	`conf`	The Influence of Parameters in Evolutionary Based Rule Extraction Method from Neural Network. ISDA Urszula Markowska-Kaczmar
2004	J	`jnl`	Discovering the Mysteries of Neural Networks. Int. J. Hybrid Intell. Syst. Urszula Markowska-Kaczmar, Marcin Chumieja
2004	Misc	`conf`	Rule Extraction from Neural Network by Genetic Algorithm with Pareto Optimization. ICAISC Urszula Markowska-Kaczmar, Pawel Wnuk-Lipinski
2003	B	`conf`	Extraction of fuzzy rules from trained neural network using evolutionary algorithm. ESANN Urszula Markowska-Kaczmar, Wojciech Trelak
2003	C	`conf`	Opening Neural Network Black Box by Evolutionary Approach. HIS Urszula Markowska-Kaczmar, Marcin Chumieja

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.