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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.
Programming of web pages lab.
Programming of web pages lec.
Programowanie stron internetowych wyk.
Programowanie stron internetowych lab.
PhD DSc Eng Marcin Zalasiński
Office hours: Środa: 10:00-12:00, 16:00-18:00

Papers (36)

2021 (1)

Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network
Tacjana Niksa-Rynkiewicz and Natalia Szewczuk-Krypa and Anna Witkowska and Krzysztof Cpałka and Marcin Zalasiński and Andrzej Cader, Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network, 143-155, 2021, Cites: 0

2020 (5)

An interpretable fuzzy system in the on-line signature scalable verification
Marcin Zalasiński and Krzysztof Cpałka and Krystian Łapa, An interpretable fuzzy system in the on-line signature scalable verification, IEEE, 1-9, 2020, Cites: 0
On-line signature partitioning using a population based algorithm
Marcin Zalasiński and Krystian Łapa and Krzysztof Cpałka and Krzysztof Przybyszewski and Gary G Yen, On-line signature partitioning using a population based algorithm, 2020, Cites: 3
The Dynamic Signature Verification Using population-Based Vertical Partitioning
Marcin Zalasiński and Krzysztof Cpałka and Tacjana Niksa-Rynkiewicz, The Dynamic Signature Verification Using population-Based Vertical Partitioning, Springer, Cham, 569-579, 2020, Cites: 0
Nanostructured Silica with Anchoring Units: The 2D Solid Solvent for Molecules and Metal Ions
Magdalena Laskowska and Oleksandr Pastukh and Andrii Fedorchuk and Mateusz Schabikowski and Paweł Kowalczyk and Marcin Zalasiński and Łukasz Laskowski, Nanostructured Silica with Anchoring Units: The 2D Solid Solvent for Molecules and Metal Ions, Multidisciplinary Digital Publishing Institute, 8137, 2020, Cites: 0
Signature Partitioning Using Selected Population-Based Algorithms
Marcin Zalasiński and Krzysztof Cpałka and Tacjana Niksa-Rynkiewicz and Yoichi Hayashi, Signature Partitioning Using Selected Population-Based Algorithms, Springer, Cham, 480-488, 2020, Cites: 0

2019 (3)

Algorithm Based on Population with a Flexible Search Mechanism
Krystian Łapa and Krzysztof Cpałka and Marcin Zalasiński, Algorithm Based on Population with a Flexible Search Mechanism, IEEE, 132253-132270, 2019, Cites: 2
The method of predicting changes of a dynamic signature using possibilities of population-based algorithms
Marcin Zalasiński and Krystian Łapa and Krzysztof Cpałka and Alina Marchlewska, The method of predicting changes of a dynamic signature using possibilities of population-based algorithms, Springer, Cham, 540-549, 2019, Cites: 3
Intelligent Approach to the Prediction of Changes in Biometric Attributes
Marcin Zalasiński and Krystian Łapa and Magdalena Laskowska, Intelligent Approach to the Prediction of Changes in Biometric Attributes, IEEE, 1073-1083, 2019, Cites: 2

2018 (4)

Prediction of values of the dynamic signature features
Marcin Zalasiński and Krystian Łapa and Krzysztof Cpałka, Prediction of values of the dynamic signature features, Pergamon, 86-96, 2018, Cites: 14
Fuzzy-genetic approach to identity verification using a handwritten signature
Marcin Zalasiński and Krzysztof Cpałka and Leszek Rutkowski, Fuzzy-genetic approach to identity verification using a handwritten signature, Springer, Cham, 375-394, 2018, Cites: 8
Stability of Features Describing the Dynamic Signature Biometric Attribute
Marcin Zalasiński and Krzysztof Cpałka and Konrad Grzanek, Stability of Features Describing the Dynamic Signature Biometric Attribute, Springer, Cham, 250-261, 2018, Cites: 0
A new method for signature verification based on selection of the most important partitions of the dynamic signature
Marcin Zalasiński and Krzysztof Cpałka, A new method for signature verification based on selection of the most important partitions of the dynamic signature, Elsevier, 13-22, 2018, Cites: 11

2017 (4)

A method for genetic selection of the most characteristic descriptors of the dynamic signature
Marcin Zalasiński and Krzysztof Cpałka and Yoichi Hayashi, A method for genetic selection of the most characteristic descriptors of the dynamic signature, Springer, Cham, 747-760, 2017, Cites: 4
A method for genetic selection of the dynamic signature global features’ subset
Marcin Zalasiński and Krzysztof Cpałka, A method for genetic selection of the dynamic signature global features’ subset, Springer, Cham, 73-82, 2017, Cites: 2
Stability evaluation of the dynamic signature partitions over time
Marcin Zalasiński and Krzysztof Cpałka and Meng Joo Er, Stability evaluation of the dynamic signature partitions over time, Springer, Cham, 733-746, 2017, Cites: 3
A method for changes prediction of the dynamic signature global features over time
Marcin Zalasiński and Krystian Łapa and Krzysztof Cpałka and Takamichi Saito, A method for changes prediction of the dynamic signature global features over time, Springer, Cham, 761-772, 2017, Cites: 3

2016 (6)

New algorithm for on-line signature verification using characteristic global features
Marcin Zalasiński, New algorithm for on-line signature verification using characteristic global features, Springer, Cham, 137-146, 2016, Cites: 17
Estimating CPU features by browser fingerprinting
Takamichi Saito and Koki Yasuda and Takayuki Ishikawa and Rio Hosoi and Kazushi Takahashi and Yongyan Chen and Marcin Zalasiński, Estimating CPU features by browser fingerprinting, IEEE, 587-592, 2016, Cites: 5
A new approach to the dynamic signature verification aimed at minimizing the number of global features
Marcin Zalasiński and Krzysztof Cpałka and Yoichi Hayashi, A new approach to the dynamic signature verification aimed at minimizing the number of global features, Springer, Cham, 218-231, 2016, Cites: 17
An idea of the dynamic signature verification based on a hybrid approach
Marcin Zalasiński and Krzysztof Cpałka and Elisabeth Rakus-Andersson, An idea of the dynamic signature verification based on a hybrid approach, Springer, Cham, 232-246, 2016, Cites: 27
New algorithm for on-line signature verification using characteristic hybrid partitions
Marcin Zalasiński and Krzysztof Cpałka, New algorithm for on-line signature verification using characteristic hybrid partitions, Springer, Cham, 147-157, 2016, Cites: 24
A new algorithm for identity verification based on the analysis of a handwritten dynamic signature
Krzysztof Cpałka and Marcin Zalasiński and Leszek Rutkowski, A new algorithm for identity verification based on the analysis of a handwritten dynamic signature, Elsevier, 47-56, 2016, Cites: 89

2015 (2)

A new method for the dynamic signature verification based on the stable partitions of the signature
Marcin Zalasiński and Krzysztof Cpałka and Meng Joo Er, A new method for the dynamic signature verification based on the stable partitions of the signature, Springer, Cham, 161-174, 2015, Cites: 17
New fast algorithm for the dynamic signature verification using global features values
Marcin Zalasiński and Krzysztof Cpałka and Yoichi Hayashi, New fast algorithm for the dynamic signature verification using global features values, Springer, Cham, 175-188, 2015, Cites: 28

2014 (5)

On-line signature verification using vertical signature partitioning
Krzysztof Cpałka and Marcin Zalasiński, On-line signature verification using vertical signature partitioning, Pergamon, 2014, Cites: 83
New method for dynamic signature verification based on global features
Marcin Zalasiński and Krzysztof Cpałka and Yoichi Hayashi, New method for dynamic signature verification based on global features, Springer, Cham, 231-245, 2014, Cites: 35
A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects
K Cpałka and K Łapa and A Przybył and M Zalasiński, A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects, Elsevier, 203-217, 2014, Cites: 70
New method for dynamic signature verification using hybrid partitioning
Marcin Zalasiński and Krzysztof Cpałka and Meng Joo Er, New method for dynamic signature verification using hybrid partitioning, Springer, Cham, 216-230, 2014, Cites: 37
New method for the on-line signature verification based on horizontal partitioning
Krzysztof Cpałka and Marcin Zalasiński and Leszek Rutkowski, New method for the on-line signature verification based on horizontal partitioning, Pergamon, 2652-2661, 2014, Cites: 96

2013 (4)

A new method for designing and complexity reduction of neuro-fuzzy systems for nonlinear modelling
Krystian Łapa and Marcin Zalasiński and Krzysztof Cpałka, A new method for designing and complexity reduction of neuro-fuzzy systems for nonlinear modelling, Springer, Berlin, Heidelberg, 329-344, 2013, Cites: 37
New algorithm for evolutionary selection of the dynamic signature global features
Marcin Zalasiński and Krystian Łapa and Krzysztof Cpałka, New algorithm for evolutionary selection of the dynamic signature global features, Springer, Berlin, Heidelberg, 113-121, 2013, Cites: 36
New approach for the on-line signature verification based on method of horizontal partitioning
Marcin Zalasiński and Krzysztof Cpałka, New approach for the on-line signature verification based on method of horizontal partitioning, Springer, Berlin, Heidelberg, 342-350, 2013, Cites: 43
Novel algorithm for the on-line signature verification using selected discretization points groups
Marcin Zalasiński and Krzysztof Cpałka, Novel algorithm for the on-line signature verification using selected discretization points groups, Springer, Berlin, Heidelberg, 493-502, 2013, Cites: 36

2012 (1)

Novel algorithm for the on-line signature verification
Marcin Zalasiński and Krzysztof Cpałka, Novel algorithm for the on-line signature verification, Springer, Berlin, Heidelberg, 362-367, 2012, Cites: 45

2011 (1)

A new method of on-line signature verification using a flexible fuzzy one-class classifier
M Zalasiński and K Cpałka, A new method of on-line signature verification using a flexible fuzzy one-class classifier, 38-53, 2011, Cites: 35

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