| Deep learning for grape variety recognition B Franczyk, M Hernes, A Kozierkiewicz, A Kozina, M Pietranik, I Roemer, ... Procedia Computer Science 176, 1211-1220, 2020 | 49 | 2020 |
| A multi-attribute based framework for ontology aligning M Pietranik, NT Nguyen Neurocomputing 146, 276-290, 2014 | 45 | 2014 |
| The knowledge increase estimation framework for ontology integration on the concept level A Kozierkiewicz-Hetmańska, M Pietranik Journal of Intelligent & Fuzzy Systems 32 (2), 1161-1172, 2017 | 20 | 2017 |
| Financial time series forecasting: Comparison of traditional and spiking neural networks K Mateńczuk, A Kozina, A Markowska, K Czerniachowska, ... Procedia Computer Science 192, 5023-5029, 2021 | 18 | 2021 |
| Semantic distance measure between ontology concept’s attributes M Pietranik, NT Nguyen Knowledge-Based and Intelligent Information and Engineering Systems: 15th …, 2011 | 15 | 2011 |
| Semi-automatic definition of attribute semantics for the purpose of ontology integration B Hnatkowska, A Kozierkiewicz, M Pietranik IEEE Access 8, 107272-107284, 2020 | 14 | 2020 |
| A method for ontology alignment based on semantics of attributes M Pietranik, NT Nguyen Cybernetics and Systems 43 (4), 319-339, 2012 | 13 | 2012 |
| The data richness estimation framework for federated data warehouse integration R Kern, A Kozierkiewicz, M Pietranik Information Sciences 513, 397-411, 2020 | 8 | 2020 |
| A formal framework for the ontology evolution A Kozierkiewicz, M Pietranik Intelligent Information and Database Systems: 11th Asian Conference, ACIIDS …, 2019 | 8 | 2019 |
| The knowledge increase estimation framework for ontology integration on the instance level A Kozierkiewicz-Hetmańska, M Pietranik, B Hnatkowska Intelligent Information and Database Systems: 9th Asian Conference, ACIIDS …, 2017 | 8 | 2017 |
| Comparison of deep learning methods for grapevine growth stage recognition M Schieck, P Krajsic, F Loos, A Hussein, B Franczyk, A Kozierkiewicz, ... Computers and Electronics in Agriculture 211, 107944, 2023 | 7 | 2023 |
| Towards the pattern-based transformation of SBVR models to association-oriented models M Jodłowiec, M Pietranik Computational Collective Intelligence: 11th International Conference, ICCCI …, 2019 | 7 | 2019 |
| Framework for ontology evolution based on a multi-attribute alignment method M Pietranik, NT Nguyen 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF), 108-112, 2015 | 7 | 2015 |
| Assessing the quality of a consensus determined using a multi-level approach A Kozierkiewicz-Hetmańska, M Pietranik 2017 IEEE International Conference on INnovations in Intelligent SysTems and …, 2017 | 6 | 2017 |
| Shelf space allocation problem with horizontal shelf division K Czerniachowska, K Lutosławski, A Kozina, K Mateńczuk, A Markowska, ... Procedia Computer Science 192, 1550-1559, 2021 | 5 | 2021 |
| Updating Ontology Alignment on the Relation Level based on Ontology Evolution. A Kozierkiewicz, M Pietranik ENASE, 241-248, 2020 | 5 | 2020 |
| The knowledge increase estimation framework for integration of ontology instances’ relations A Kozierkiewicz, M Pietranik Databases and Information Systems: 13th International Baltic Conference, DB …, 2018 | 5 | 2018 |
| Attribute mapping as a foundation of ontology alignment M Pietranik, NT Nguyen Asian Conference on Intelligent Information and Database Systems, 455-465, 2011 | 5 | 2011 |
| Methods of managing the evolution of ontologies and their alignments M Pietranik, A Kozierkiewicz Applied Intelligence 53 (17), 20382-20401, 2023 | 4 | 2023 |
| Fuzzy based approach to ontology relations alignment B Hnatkowska, A Kozierkiewicz, M Pietranik 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-7, 2021 | 4 | 2021 |
Adrianna KozierkiewiczWrocław University of TechnologyVerified email at pwr.wroc.pl
