Newton-like method for singular 2-regular system of nonlinear equations. - Stanislaw M. Grzegórski; Edyta Lukasik (Ann. UMCS Informatica, 2003)

Superquadraticly convergent methods for minimization fonctions. - Stanislaw M. Grzegórski; Edyta Lukasik (Ann. UMCS Informatica, 2004)

Efficiency of 2-order iterative methods. - Stanislaw M. Grzegórski; Edyta Lukasik (Ann. UMCS Informatica, 2004)

Reengineering of computer science curriculum according to technology changes and market needs. - Marek Milosz; Edyta Lukasik (EDUCON, 2015)

Analysis of rowing based on handle trajectory. - Maria Skublewska-Paszkowska; Edyta Lukasik; Jerzy Montusiewicz (HSI, 2016)

The rigid body gap filling algorithm. - Jakub Smolka; Edyta Lukasik (HSI, 2016)

Analysis of Selected Elements of a Rower's Posture Using Motion Capture - a Case Study. - Jerzy Montusiewicz; Jakub Smolka; Maria Skublewska-Paszkowska; Edyta Lukasik; Katarzyna R. Baran; Izabela Pszczola-Pasierbiewicz (ICIST, 2016)

Support of computer science students by practitioners from industry. - Edyta Lukasik (EDUCON, 2017)

Algorithm Defining the Correctness of an Ergometer Rower's Technique Using Three-Dimensional Data. - Edyta Lukasik; Jakub Smolka; Jerzy Montusiewicz (ICIST, 2017)

New Automatic Algorithms for Computing Characteristics of Three Dimensional Pelvic and Lower Limb Motions in Race Walking. - Maria Skublewska-Paszkowska; Edyta Lukasik; Jakub Smolka; Monika Nawrocka (HSI, 2018)

Motion Capture Technology as a Tool for Quantitative Assessment of the Rehabilitation Progress of Gait by Using Soft Orthoses. - Maria Skublewska-Paszkowska; Edyta Lukasik; Marek Milosz; Jakub Smolka; Jaroslaw Napiorkowski; Jolanta Taczala; Agnieszka Zdzienicka-Chyla; Anna Kosiecz (HSI, 2018)

Recognition of Tennis Shots Using Convolutional Neural Networks Based on Three-Dimensional Data. - Maria Skublewska-Paszkowska; Edyta Lukasik; Bartlomiej Szydlowski; Jakub Smolka; Pawel Powroznik (ICMMI, 2019)

Learning Three Dimensional Tennis Shots Using Graph Convolutional Networks. - Maria Skublewska-Paszkowska; Pawel Powroznik; Edyta Lukasik (Sensors, 2020)

Tennis Multivariate Time Series Clustering. - Maria Skublewska-Paszkowska; Pawel Karczmarek; Edyta Lukasik (FUZZ-IEEE, 2021)

Estimation of the Path-Loss Exponent by Bayesian Filtering Method. - Piotr Wojcicki; Tomasz Zientarski; Malgorzata Charytanowicz; Edyta Lukasik (Sensors, 2021)

On the Detection of Anomalies with the Use of Choquet Integral and Their Interpretability in Motion Capture Data. - Michal Dolecki; Pawel Karczmarek; Lukasz Galka; Magdalena Zawadka; Jakub Smolka; Maria Skublewska-Paszkowska; Edyta Lukasik; Pawel Powroznik; Piotr Gawda; Dariusz Czerwinski (FUZZ-IEEE, 2022)

Analysis of Sub-Integral Functions in the Aggregation of Classification Results Using Generalizations of the Choquet Integral on the Example of Emotion Classification. - Pawel Karczmarek; Pawel Powroznik; Maria Skublewska-Paszkowska; Slawomir Przylucki; Edyta Lukasik (FUZZ-IEEE, 2022)

Aggregation of Tennis Groundstrokes on the Basis of the Choquet Integral and Its Generalizations. - Maria Skublewska-Paszkowska; Pawel Powroznik; Pawel Karczmarek; Edyta Lukasik (FUZZ-IEEE, 2022)

Attention Temporal Graph Convolutional Network for Tennis Groundstrokes Phases Classification. - Maria Skublewska-Paszkowska; Pawel Powroznik; Edyta Lukasik (FUZZ-IEEE, 2022)

Aggregation of Tennis Multivariate Time-Series Using the Choquet Integral and Its Generalizations. - Maria Skublewska-Paszkowska; Pawel Karczmarek; Pawel Powroznik; Edyta Lukasik; Jakub Smolka; Michal Dolecki (FUZZ, 2023)

Fuzzy C-Means Clustering for Motion Capture Tennis Time-Series Data. - Maria Skublewska-Paszkowska; Pawel Powroznik; Pawel Karczmarek; Edyta Lukasik; Jakub Smolka (IEEE Access, 2024)