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 | 44 | 2020 |
Towards Industry 4.0: Functional and technological basis for ERP 4.0 Systems A Bytniewski, K Matouk, A Rot, M Hernes, A Kozina Towards Industry 4.0—Current Challenges in Information Systems, 3-19, 2020 | 22 | 2020 |
Deep learning for customer churn prediction in e-commerce decision support M Pondel, M Wuczyński, W Gryncewicz, £ £ysik, M Hernes, A Rot, ... Business Information Systems, 3-12, 2021 | 20 | 2021 |
Food demand prediction using the nonlinear autoregressive exogenous neural network K Lutoslawski, M Hernes, J Radomska, M Hajdas, E Walaszczyk, ... IEEE Access 9, 146123-146136, 2021 | 15 | 2021 |
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 | 13 | 2021 |
Deep learning and forecasting in practice: an alternative costs case T Zema, A Kozina, A Sulich, I Römer, M Schieck Procedia Computer Science 207, 2958-2967, 2022 | 8 | 2022 |
The functionalities of cognitive technology in management control system A Bytniewski, K Matouk, A Chojnacka-Komorowska, M Hernes, ... Asian Conference on Intelligent Information and Database Systems, 230-240, 2020 | 8 | 2020 |
Supporting investment decisions based on cognitive technology P Oleksyk, M Hernes, B Nita, H Dudycz, A Kozina, J Janus Towards Industry 4.0—Current Challenges in Information Systems, 41-59, 2020 | 7 | 2020 |
Deep learning for repayment prediction in leasing companies M Hernes, A Kozierkiewicz, M Maleszka, A Rot, A Kozina, K Matenczuk, ... University of Piraeus. International Strategic Management Association, 2021 | 6 | 2021 |
Shelf space allocation problem with horizontal shelf division K Czerniachowska, K Lutos³awski, A Kozina, K Mateńczuk, A Markowska, ... Procedia Computer Science 192, 1550-1559, 2021 | 4 | 2021 |
Using the FMEA method as a response to a customer complaint: a case study S Dziuba, M Ingaldi, A Kozina, M Hernes Revista Gestao & Tecnologia-Journal of Management and Technology 21 (1), 2021 | 4 | 2021 |
8D report as the product improvement tool ST Dziuba, M Ingaldi, A Kozina, M Hernes Sistemas & Gestao 16 (2), 2021 | 4 | 2021 |
Data Quality Management in ERP Systems–Accounting Case M Hernes, A Bytniewski, K Mateńczuk, A Rot, S Dziuba, M Fojcik, ... International Conference on Computational Collective Intelligence, 353-362, 2020 | 3 | 2020 |
Between deep learning and alternative costs: bibliometric analysis A Kozina, T Zema, A Sulich Procedia Computer Science 207, 1842-1849, 2022 | 2 | 2022 |
Reduction of Information Asymmetry in the Used Car Market Using the Random Forest Method M Bies, W Gryncewicz, A Kozina, M Hernes, A Rot, R Zyga³a 2021 11th International Conference on Advanced Computer Information …, 2021 | 2 | 2021 |
Cognitive Agent for the Quality Management in Flexographic Printing on Packages J Janus, M Hernes, W Gryncewicz, A Rot, AM Kozina, A Markowska, ... Handbook of research on autopoiesis and self-sustaining processes for …, 2021 | 2 | 2021 |
Smart Payment Terminal in energy payment for electric and hybrid cars P Dankiewicz, M Hernes, E Walaszczyk, P Tutak, I Chomiak-Orsa, A Rot, ... Informatyka Ekonomiczna. Prace Naukowe Uniwersytetu Ekonomicznego we Wroc³awiu, 2020 | 2 | 2020 |
The default of leasing contracts prediction using machine learning A Kozina, £ Ku¼miński, M Nadolny, K Mia³kowska, P Tutak, J Janus, ... Procedia Computer Science 225, 424-433, 2023 | | 2023 |
Network Analysis Towards Development of Interest Rates in the Countries of the European Union T Zema, A Kozina, S Hamovį on European Integration 2022, 787, 2022 | | 2022 |
Generative Adversarial Networks for students' structure prediction. Preliminary research. A Kozina, Z Kes, M Hernes, P Golec, K Nowosielski, O Sidor, K Zhanat FedCSIS (Position Papers), 113-120, 2022 | | 2022 |