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. Książek, W., F. Turza, and P. Pławiak, "NCA-GA-SVM: A new two-level feature selection method based on neighborhood component analysis and genetic algorithm in hepatocellular carcinoma fatality prognosis", International Journal for Numerical Methods in Biomedical Engineering, vol. 38, 2022.
2. Saber, S., K. Amin, P. Pławiak, R. Tadeusiewicz, and M. Hammad, "Graph Convolutional Network with Triplet Attention learning for Person Re-Identification.", Information Sciences, 2022.
3. Salehi, T., M. Zomorodi, P. Pławiak, M. Abbaszade, and V. Salari, "An optimizing method for performance and resource utilization in quantum machine learning circuits.", Scientific Reports, vol. 12, issue 1, 2022/10/10.
4. 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.", Biomedical Signal Processing and Control, vol. 72, 2022.
5. Sakr, A. S., P. Pławiak, R. Tadeusiewicz, and M. Hammad, "Cancelable ECG biometric based on combination of deep transfer learning with DNA and amino acid approaches for human authentication.", Information Sciences, vol. 585, 2022.
6. Kora, P., C. Ping Ooi, O. Faust, U. Raghavendra, A. Gudigar, W. Yee Chan, K. Meenakshi, K. Swaraja, P. Pławiak, and R. U. Acharya, "Transfer learning techniques for medical image analysis: A review", Biocybernetics and Biomedical Engineering, vol. 42, 2022.
7. 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)
8. Sahoo, J. Prakash, A. Jaya Prakash, P. Pławiak, and S. Samantray, "Real-Time Hand Gesture Recognition Using Fine-Tuned Convolutional Neural Network.", Sensors, vol. 22, 2022.
9. Pławiak, P., N. Salankar, S. Mian Qaisar, R. Tadeusiewicz, and M. Hammad, "EEG based alcoholism detection by oscillatory modes decomposition second order difference plots and machine learning.", Biocybernetics and Biomedical Engineering, vol. 42, 2022.
10. Dakshayani, V., G. Rao Locharla, P. Pławiak, V. Datti, and C. Karri, "Design of a Gabor Filter-Based Image Denoising Hardware Model", Electronics, vol. 11, 2022.
11. Mohammed, Y. Salaheldin, H. Abdelkader, P. Pławiak, and M. Hammad, "A novel model to optimize multiple imputation algorithm for missing data using evolution methods.", Biomedical Signal Processing and Control, vol. 76, 2022.
12. Sakr, A. S., N. F. Soliman, M. S. Al-Gaashani, P. Pławiak, A. A. Ateya, and M. Hammad, "An Efficient Deep Learning Approach for Colon Cancer Detection", Applied Sciences, vol. 12, 2022.
13. Hammad, M., M. Bakrey, A. Bakhiet, R. Tadeusiewicz, A. A. Abd EL-Latif, and P. Pławiak, "A novel end-to-end deep learning approach for cancer detection based on microscopic medical images.", Biocybernetics and Biomedical Engineering, vol. 42, 2022.
14. Prakash, A. Jaya, K. Kumar Patro, M. Hammad, R. Tadeusiewicz, and P. Pławiak, "BAED: A secured biometric authentication system using ECG signal based on deep learning techniques.", Biocybernetics and Biomedical Engineering, vol. 42, 2022.
15. Hammad, M., S. Allaoua Chelloug, R. Alkanhel, A. Jaya Prakash, A. Muthanna, I. A. Elgendy, and P. Pławiak, "Automated Detection of Myocardial Infarction and Heart Conduction Disorders Based on Feature Selection and a Deep Learning Model", Sensors, vol. 22, 2022.
16. Qaisar, S. Mian, S. I. Khan, D. Dallet, R. Tadeusiewicz, and P. Pławiak, "Signal-piloted processing metaheuristic optimization and wavelet decomposition based elucidation of arrhythmia for mobile healthcare", Biocybernetics and Biomedical Engineering., vol. 42, 2022.
17. Warmiński, G., P. Urbanek, M. Orczykowski, R. Bodalski, Ł. Kalińczuk, K. Zieliński, G. S. Mintz, Z. Jedynak, A. Hasiec, J. Zakrzewska-Koperska, et al., "Association of left atrial enlargement and increased left ventricular wall thickness with arrhythmia recurrence after cryoballoon ablation for atrial fibrillation.", Kardiologia Polska (Polish Heart Journal), 2022.
18. Dadkhah, D., M. Zomorodi, S. Ebrahim Hosseini, P. Pławiak, and X. Zhou, "Reordering and Partitioning of Distributed Quantum Circuits.", IEEE Access, vol. 10, 2022.
19. Warmiński, G., Ł. Kalińczuk, M. Orczykowski, P. Urbanek, R. Bodalski, K. Zieliński, M. Gandor, P. F, Jaworski, G. S. Mintz, et al., "Artificial intelligence analysis of ECG signals to predict arrhythmia recurrence after cryoballoon ablation of atrial fibrillation.", European Heart Journal, vol. 43, 2022.
20. Oztekin, F., O. Katar, F. Sadak, M. Aydogan, T. Talo Yildirim, P. Pławiak, O. Yildirim, M. Talo, and M. Karabatak, "Automatic semantic segmentation for dental restorations in panoramic radiography images using U-Net model.", International Journal of Imaging Systems and Technology, vol. 32, 2022.

2021

21. 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.
22. 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)
23. 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)
24. 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.
25. 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)

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Data aktualizacji: 21/07/2022 - 10:35; autor zmian: Maciej Skrabski (mskrabski@iitis.pl)