Found 9 results
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Nasarian E, Abdar M, Fahami MAmin, Alizadehsani R, Hussain S, Basiri MEhsan, Zomorodi-Moghadam M, Zhou X, Pławiak P, U. Acharya R et al..  2020.  Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach. Elsevier, Pattern Recognition Letters. 133:33-40. (913.08 KB)
Książek W, Hammad M, Pławiak P, U. Acharya R, Tadeusiewicz R.  2020.  Development of novel ensemble model using stacking learning and evolutionary computation techniques for automated hepatocellular carcinoma detection. Biocybernetics and Biomedical Engineering. 40(4):1512-1524. (1.1 MB)
Pławiak P, Abdar M, Pławiak J, Makarenkov V, U Acharya R.  2020.  DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring. Elsevier, Information Sciences. 516:401-418. (1.21 MB)
Tuncer T, Ertam F, Dogan S, Aydemir E, Pławiak P.  2020.  Ensemble residual network-based gender and activity recognition method with signals. Journal of Supercomputing. 76(2020):2119–2138. (2.74 MB)
Alizadehsani R, Roshanzamir M, Abdar M, Beykikhoshk A, Khosravi A, Nahavandi S, Pławiak P, San Tan R, U Acharya R.  2020.  Hybrid genetic‐discretized algorithm to handle data uncertainty in diagnosing stenosis of coronary arteries. Wiley, Expert Systems.  (2.36 MB)
Żelasko D, Pławiak P, Kołodziej J.  2020.  Machine learning techniques for transmission parameters classification in multi-agent managed network. 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID).  (877.3 KB)
Nowak S, Nowak M, Baldini G, Hernandez-Ramos JL, Neisse R.  2020.  Mitigation of Privacy Threats due to Encrypted Traffic Analysis through a Policy-Based Framework and MUD Profiles. Symmetry. 12(9) (395.99 KB)
Tuncer T, Dogan S, Abdar M, Pławiak P.  2020.  A novel facial image recognition method based on perceptual hash using quintet triple binary pattern. Multimedia Tools and Applications. 79(39):29573-29593. (1.69 MB)
Gelenbe E, Yin Y.  2016.  Deep learning with random neural networks. International Joint Conference on Neural Networks (IJCNN). :1633-1638.