user photo
Contact:
Room: 520

Position:
Associate Professor Didactics Vice-Head of Department

Research teams:
Zespół algorytmów inteligencji obliczeniowej i ich zastosowań
Leader of: Zespół algorytmów inteligencji obliczeniowej i ich zastosowań

Classes:
Aplikacje WWW lab
Aplikacje WWW wyk
Aplikacje serwerowe lab
Aplikacje serwerowe wyk
PhD DSc Eng Marcin Zalasiński

Papers (41)

2023 (2)

Dynamic Signature Verification Using Selected Regions
Zalasinski M., Duda P., Lota S., Cpalka K., Dynamic Signature Verification Using Selected Regions, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, 388-397, 2023, Cites: 1
A New Method of Verification of Dynamic Signatures Changing over Time with Decomposition and Selection of Characteristic Descriptors
Mastalerczyk M., Szczepanik T., Zalasinski M., A New Method of Verification of Dynamic Signatures Changing over Time with Decomposition and Selection of Characteristic Descriptors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14126 LNAI, 14126 LNAI, 251-257, 2023, Cites: 0

2022 (1)

Evolutionary Algorithm for Selecting Dynamic Signatures Partitioning Approach
Zalasinski M., Laskowski L., Niksa-Rynkiewicz T., Cpalka K., Byrski A., Przybyszewski K., Trippner P., Dong S., Evolutionary Algorithm for Selecting Dynamic Signatures Partitioning Approach, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 267-279, 2022, Cites: 5

2021 (2)

Monitoring regenerative heat exchanger in steam power plant by making use of the recurrent neural network
Niksa-Rynkiewicz T., Szewczuk-Krypa N., Witkowska A., Cpalka K., Zalasinski M., Cader A., Monitoring regenerative heat exchanger in steam power plant by making use of the recurrent neural network, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 143-155, 2021, Cites: 12
Dynamic Signature Vertical Partitioning Using Selected Population-Based Algorithms
Zalasinski M., Niksa-Rynkiewicz T., Cpalka K., Dynamic Signature Vertical Partitioning Using Selected Population-Based Algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12855 LNAI, 12855 LNAI, 511-518, 2021, Cites: 0

2020 (8)

Signature Partitioning Using Selected Population-Based Algorithms
Zalasinski M., Cpalka K., Niksa-Rynkiewicz T., Hayashi Y., Signature Partitioning Using Selected Population-Based Algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 480-488, 2020, Cites: 0
Intelligent Approach to the Prediction of Changes in Biometric Attributes
Zalasinski M., Lapa K., Laskowska M., Intelligent Approach to the Prediction of Changes in Biometric Attributes, IEEE Transactions on Fuzzy Systems, 28, 28, 1073-1083, 2020, Cites: 3
Magnetic behaviour of Mn<inf>12</inf>-stearate single-molecule magnets immobilized on the surface of 300 nm spherical silica nanoparticles
Laskowska M., Pastukh O., Konieczny P., Dulski M., Zalsinski M., Laskowski L., Magnetic behaviour of Mn<inf>12</inf>-stearate single-molecule magnets immobilized on the surface of 300 nm spherical silica nanoparticles, Materials, 13, 13, 2020, Cites: 9
On-Line Signature Partitioning Using a Population Based Algorithm
Zalasinski M., Lapa K., Cpalka K., Przybyszewski K., Yen G.G., On-Line Signature Partitioning Using a Population Based Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 5-13, 2020, Cites: 10
An interpretable fuzzy system in the on-line signature scalable verification
Zalasinski M., Cpalka K., Lapa K., An interpretable fuzzy system in the on-line signature scalable verification, IEEE International Conference on Fuzzy Systems, 2020-July, 2020-July, 2020, Cites: 2
An Algorithm for the Evolutionary-Fuzzy Generation of on-Line Signature Hybrid Descriptors
Zalasinski M., Cpalka K., Laskowski L., Wunsch D.C., Przybyszewski K., An Algorithm for the Evolutionary-Fuzzy Generation of on-Line Signature Hybrid Descriptors, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 173-187, 2020, Cites: 5
The Dynamic Signature Verification Using population-Based Vertical Partitioning
Zalasinski M., Cpalka K., Niksa-Rynkiewicz T., The Dynamic Signature Verification Using population-Based Vertical Partitioning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12532 LNCS, 12532 LNCS, 569-579, 2020, Cites: 1
Nanostructured silica with anchoring units: The 2D solid solvent for molecules and metal ions
Laskowska M., Pastukh O., Fedorchuk A., Schabikowski M., Kowalczyk P., Zalasinski M., Laskowski L., Nanostructured silica with anchoring units: The 2D solid solvent for molecules and metal ions, International Journal of Molecular Sciences, 21, 21, 1-38, 2020, Cites: 11

2019 (2)

Algorithm Based on Population with a Flexible Search Mechanism
Lapa K., Cpalka K., Zalasinski M., Algorithm Based on Population with a Flexible Search Mechanism, IEEE Access, 7, 7, 132253-132270, 2019, Cites: 5
The Method of Predicting Changes of a Dynamic Signature Using Possibilities of Population-Based Algorithms
Zalasinski M., Lapa K., Cpalka K., Marchlewska A., The Method of Predicting Changes of a Dynamic Signature Using Possibilities of Population-Based Algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 540-549, 2019, Cites: 2

2018 (5)

A new method for signature verification based on selection of the most important partitions of the dynamic signature
Zalasinski M., Cpalka K., A new method for signature verification based on selection of the most important partitions of the dynamic signature, Neurocomputing, 289, 289, 13-22, 2018, Cites: 11
Prediction of values of the dynamic signature features
Zalasinski M., Lapa K., Cpalka K., Prediction of values of the dynamic signature features, Expert Systems with Applications, 104, 104, 86-96, 2018, Cites: 17
Stability of features describing the dynamic signature biometric attribute
Zalasinski M., Cpalka K., Grzanek K., Stability of features describing the dynamic signature biometric attribute, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 250-261, 2018, Cites: 0
Fuzzy-genetic approach to identity verification using a handwritten signature
Zalasinski M., Cpalka K., Rutkowski L., Fuzzy-genetic approach to identity verification using a handwritten signature, Studies in Computational Intelligence, 738, 738, 375-394, 2018, Cites: 6
A method for genetic selection of the dynamic signature global features’ subset
Zalasinski M., Cpalka K., A method for genetic selection of the dynamic signature global features’ subset, Advances in Intelligent Systems and Computing, 655, 655, 73-82, 2018, Cites: 3

2017 (3)

A method for genetic selection of the most characteristic descriptors of the dynamic signature
Zalasinski M., Cpalka K., Hayashi Y., A method for genetic selection of the most characteristic descriptors of the dynamic signature, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 747-760, 2017, Cites: 4
Stability evaluation of the dynamic signature partitions over time
Zalasinski M., Cpalka K., Er M.J., Stability evaluation of the dynamic signature partitions over time, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 733-746, 2017, Cites: 4
A method for changes prediction of the dynamic signature global features over time
Zalasinski M., Lapa K., Cpalka K., Saito T., A method for changes prediction of the dynamic signature global features over time, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 761-772, 2017, Cites: 3

2016 (6)

Estimating CPU features by browser fingerprinting
Saito T., Yasuda K., Ishikawa T., Hosoi R., Takahashi K., Chen Y., Zalasinski M., Estimating CPU features by browser fingerprinting, Proceedings - 2016 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2016, 587-592, 2016, Cites: 8
A new approach to the dynamic signature verification aimed at minimizing the number of global features
Zalasinski M., Cpalka K., Hayashi Y., A new approach to the dynamic signature verification aimed at minimizing the number of global features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 218-231, 2016, Cites: 18
New algorithm for on-line signature verification using characteristic global features
Zalasinski M., New algorithm for on-line signature verification using characteristic global features, Advances in Intelligent Systems and Computing, 432, 432, 137-146, 2016, Cites: 14
An idea of the dynamic signature verification based on a hybrid approach
Zalasinski M., Cpalka K., Rakus-Andersson E., An idea of the dynamic signature verification based on a hybrid approach, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 232-246, 2016, Cites: 28
New algorithm for on-line signature verification using characteristic hybrid partitions
Zalasinski M., Cpalka K., New algorithm for on-line signature verification using characteristic hybrid partitions, Advances in Intelligent Systems and Computing, 432, 432, 147-157, 2016, Cites: 27
A new algorithm for identity verification based on the analysis of a handwritten dynamic signature
Cpalka K., Zalasinski M., Rutkowski L., A new algorithm for identity verification based on the analysis of a handwritten dynamic signature, Applied Soft Computing Journal, 43, 43, 47-56, 2016, Cites: 89

2015 (2)

A new method for the dynamic signature verification based on the stable partitions of the signature
Zalasinski M., Cpalka K., Er M.J., A new method for the dynamic signature verification based on the stable partitions of the signature, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 161-174, 2015, Cites: 16
New fast algorithm for the dynamic signature verification using global features values
Zalasinski M., Cpalka K., Hayashi Y., New fast algorithm for the dynamic signature verification using global features values, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 175-188, 2015, Cites: 33

2014 (5)

New method for dynamic signature verification using hybrid partitioning
Zalasinski M., Cpalka K., Er M.J., New method for dynamic signature verification using hybrid partitioning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 216-230, 2014, Cites: 33
New method for dynamic signature verification based on global features
Zalasinski M., Cpalka K., Hayashi Y., New method for dynamic signature verification based on global features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 231-245, 2014, Cites: 35
A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects
Cpalka K., Lapa K., Przybyl A., Zalasinski M., A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects, Neurocomputing, 135, 135, 203-217, 2014, Cites: 81
New method for the on-line signature verification based on horizontal partitioning
Cpalka K., Zalasinski M., Rutkowski L., New method for the on-line signature verification based on horizontal partitioning, Pattern Recognition, 47, 47, 2652-2661, 2014, Cites: 81
On-line signature verification using vertical signature partitioning
Cpalka K., Zalasinski M., On-line signature verification using vertical signature partitioning, Expert Systems with Applications, 41, 41, 4170-4180, 2014, Cites: 86

2013 (4)

Novel algorithm for the on-line signature verification using selected discretization points groups
Zalasinski M., Cpalka K., Novel algorithm for the on-line signature verification using selected discretization points groups, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 493-502, 2013, Cites: 39
New algorithm for evolutionary selection of the dynamic signature global features
Zalasinski M., Lapa K., Cpalka K., New algorithm for evolutionary selection of the dynamic signature global features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 113-121, 2013, Cites: 37
A new method for designing and complexity reduction of neuro-fuzzy systems for nonlinear modelling
Lapa K., Zalasinski M., Cpalka K., A new method for designing and complexity reduction of neuro-fuzzy systems for nonlinear modelling, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 329-344, 2013, Cites: 37
New approach for the on-line signature verification based on method of horizontal partitioning
Zalasinski M., Cpalka K., New approach for the on-line signature verification based on method of horizontal partitioning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 342-350, 2013, Cites: 38

2012 (1)

Novel algorithm for the on-line signature verification
Zalasinski M., Cpalka K., Novel algorithm for the on-line signature verification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 362-367, 2012, Cites: 45

Schedule