dr hab. inż. Paweł Pławiak

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0000-0002-4317-2801

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profesor instytutu
Zespół badawczy

Zainteresowania: 

Machine Learning; Ensemble Learning; Deep Learning; Evolutionary Computation; Data Science

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Publikacje
Biblio RSS

2022

1. Tuncer, T., S. Dogan, P. Pławiak, and A. Subasi, "A novel Discrete Wavelet-Concatenated Mesh Tree and ternary chess pattern based ECG signal recognition method", Elsevier, Biomedical Signal Processing and Control, vol. 72, 02/2022.  (2.11 MB)

2021

2. Hammad, M., P. Pławiak, K. Wang, and U. Rajendra Acharya, "ResNet‐Attention model for human authentication using ECG signals", Wiley, Expert Systems, vol. 38, issue 6, pp. e12547, 2021.  (2.75 MB)
3. Abdar, M., M. Amin Fahami, S. Chakrabarti, A. Khosravi, P. Pławiak, R. U. Acharya, R. Tadeusiewicz, and S. Nahavandi, "BARF: A new direct and cross-based binary residual feature fusion with uncertainty-aware module for medical image classification", Elsevier, Information Sciences, vol. 577, 10/2021.  (4.62 MB)
4. Ghodsollahee, I., Z. Davarzani, M. Zomorodi, P. Pławiak, M. Houshmand, and M. Houshmand, "Connectivity matrix model of quantum circuits and its application to distributed quantum circuit optimization", Springer, Quantum Information Processing, vol. 20, 08/2021.  (2.21 MB)
5. Pałka, F., W. Książek, P. Pławiak, M. Romaszewski, and K. Książek, "Hyperspectral Classification of Blood-Like Substances Using Machine Learning Methods Combined with Genetic Algorithms in Transductive and Inductive Scenarios", Sensors, vol. 21, 03/2021.
6. Żelasko, D., and P. Pławiak, "Ensemble learning techniques for transmission quality classification in Pay&Require multi-layer network", International Journal of Applied Mathematics and Computer Science, vol. 31, issue 1, 03/2021.  (1.01 MB)
7. Tuncer, T., S. Dogan, G. Naik, and P. Pławiak, "Epilepsy attacks recognition based on 1D octal pattern, wavelet transform and EEG signals", Springer, Multimedia Tools and Applications , 04/2021.  (1.58 MB)
8. Wierzbiński, M., P. Pławiak, M. Hammad, and R. U Acharya, "Development of accurate classification of heavenly bodies using novel machine learning techniques", Springer, Soft Computing, vol. 25, issue 2021, 05/2021.
9. Hammad, M., R. N. V. P. S. Kandala, A. Abdelatey, M. Abdar, M. Zomorodi‐Moghadam, R. San Tan, R. U. Acharya, J. Pławiak, R. Tadeusiewicz, V. Makarenkov, et al., "Automated detection of shockable ECG signals: A review", Elsevier, Information Sciences, 05/2021.  (3.76 MB)
10. Żelasko, D., W. Książek, and P. Pławiak, "Transmission Quality Classification with Use of Fusion of Neural Network and Genetic Algorithm in Pay&Require Multi-Agent Managed Network", MDPI, Sensors, vol. 21, 06/2021.  (503.51 KB)
11. Książek, W., M. Gandor, and P. Pławiak, "Comparison of various approaches to combine logistic regression with genetic algorithms in survival prediction of hepatocellular carcinoma", Elsevier, Computers in Biology and Medicine, vol. 134, 07/2021.  (4.14 MB)
12. Zomorodi-Moghadam, M., M. Abdar, Z. Davarzani, X. Zhou, P. Pławiak, and , "Hybrid particle swarm optimization for rule discovery in the diagnosis of coronary artery disease", Wiley, Expert Systems, vol. 38, 01/2021.  (1.69 MB)
13. Sinha, V. Kumar, K. Kumar Patro, P. Pławiak, and A. Jaya Prakash, "Smartphone-Based Human Sitting Behaviors Recognition Using Inertial Sensor", MDPI, Sensors, vol. 21, issue 19, 10/2021.
14. Roui, M. Beheshti, M. Zomorodi, M. Sarvelayati, M. Abdar, H. Noori, P. Pławiak, R. Tadeusiewicz, X. Zhou, A. Khosravi, S. Nahavandi, et al., "A novel approach based on genetic algorithm to speed up the discovery of classification rules on GPUs", Elsevier, Knowledge-Based Systems, vol. 231, 11/23021, 2021.  (3.12 MB)

2020

15. Alizadehsani, R., M. Roshanzamir, M. Abdar, A. Beykikhoshk, A. Khosravi, S. Nahavandi, P. Pławiak, R. San Tan, and R. U Acharya, "Hybrid genetic-discretized algorithm to handle data uncertainty in diagnosing stenosis of coronary arteries", Wiley, Expert Systems, 04/2020.  (2.36 MB)
16. Żelasko, D., P. Pławiak, and J. Kołodziej, "Machine learning techniques for transmission parameters classification in multi-agent managed network", 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID), Melbourne, Australia, IEEE, 05/2020.  (877.3 KB)
17. Tuncer, T., S. Dogan, M. Abdar, and P. Pławiak, "A novel facial image recognition method based on perceptual hash using quintet triple binary pattern", Multimedia Tools and Applications, vol. 79, issue 39, pp. 29573-29593, 10/2020.  (1.69 MB)
18. Książek, W., M. Hammad, P. Pławiak, R. U. Acharya, and R. Tadeusiewicz, "Development of novel ensemble model using stacking learning and evolutionary computation techniques for automated hepatocellular carcinoma detection", Biocybernetics and Biomedical Engineering, vol. 40, issue 4, pp. 1512-1524, 10/2020.  (1.1 MB)
19. Pławiak, P., M. Abdar, J. Pławiak, V. Makarenkov, and R. U Acharya, "DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring", Elsevier, Information Sciences, vol. 516, pp. 401 - 418, 2020.  (1.21 MB)
20. Samami, M., E. Akbari, M. Abdar, P. Pławiak, H. Nematzadeh, M. Ehsan Basiri, and V. Makarenkov, "A mixed solution-based high agreement filtering method for class noise detection in binary classification", Elsevier, Physica A: Statistical Mechanics and its Applications, pp. 124219, 2020.  (5.51 MB)
21. Tuncer, T., F. Ertam, S. Dogan, E. Aydemir, and P. Pławiak, "Ensemble residual network-based gender and activity recognition method with signals", Journal of Supercomputing, vol. 76, issue 2020, pp. 2119–2138, 03/2020.  (2.74 MB)
22. Nasarian, E., M. Abdar, M. Amin Fahami, R. Alizadehsani, S. Hussain, M. Ehsan Basiri, M. Zomorodi-Moghadam, X. Zhou, P. Pławiak, R. U. Acharya, et al., "Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach", Elsevier, Pattern Recognition Letters, vol. 133, pp. 33-40, 05/2020.  (913.08 KB)

2019

23. Kandala, R. N. V. P. S., R. Dhuli, P. Pławiak, G. R. Naik, H. Moeinzadeh, G. D. Gargiulo, and S. Gunnam, "Towards Real-Time Heartbeat Classification: Evaluation of Nonlinear Morphological Features and Voting Method", MDPI, Sensors, vol. 23, issue 19, pp. 5079, 11/2019.  (1.3 MB)