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Luck032/CardioPRINT-biometric-identification-with-machine-learning: CardioPRINT-biometric-identification-with-machine-learning

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softwaredataset
Créateur:
TanLazKneMil
Éditeur:
Zenodo
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This repository contains Python and R programming codes that reproduce results for the paper titled " CardioPRINT: Biometric identification based on the individual characteristics derived from cardiogram". If you find provided code and signals useful for your own research and teaching class, please cite the following references: Tanasković, I., Lazarević, L. B., Knežević, G., Milosavljević, N., Dubljević, O., Bjegojević, B., & Miljković, N. (2023). CardioPRINT-based Biometric Identification with Machine Learning (Version 1.0) [Computer software]. github.com, doi.org Tanasković, I., Lazarević, L. B., Knežević, G., Milosavljević, N., Dubljević, O., Bjegojević, B., & Miljković, N. (2024). CardioPRINT: Biometric identification based on the individual characteristics derived from the cardiogram. Expert Systems with Applications, 126018. doi.org Bjegojević B, Milosavljević N, Dubljević O, Purić D, Knežević G. In pursuit of objectivity: Physiological Measures as a Means of Emotion Induction Procedure Validation. Empirical Studies in Psychology 2020:17. Tanasković, I., Lazarević, L. B., Knežević, G., Milosavljević, N., Dubljević, O., Bjegojević, B., & Miljković, N. (2023). Dataset for CardioPRINT-based Biometric Identification [Dataset]. doi.org Nadica Miljković acknowledges the support from Grant No. 451–03–47/ 2023–01/200103 funded by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia.  Ljiljana B. Lazarević and Goran Knežević acknowledge the support from Grant No. 451-03-47/2023-01/200163 funded by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia.

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