prikaz prve stranice dokumenta Prediction of human performance based on psychophysiological features of resilience and machine learning
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doctoral thesis
Prediction of human performance based on psychophysiological features of resilience and machine learning
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:767064

University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Electric Machines, Drives and Automation

Institutional repository: FER Repository

Cite this document

Šarlija, M. (2021). Prediction of human performance based on psychophysiological features of resilience and machine learning (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:767064

Šarlija, Marko. "Prediction of human performance based on psychophysiological features of resilience and machine learning." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:767064

Šarlija, Marko. "Prediction of human performance based on psychophysiological features of resilience and machine learning." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:767064

Šarlija, M. (2021). 'Prediction of human performance based on psychophysiological features of resilience and machine learning', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 04 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:767064

Šarlija M. Prediction of human performance based on psychophysiological features of resilience and machine learning [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 December 04] Available at: https://urn.nsk.hr/urn:nbn:hr:168:767064

M. Šarlija, "Prediction of human performance based on psychophysiological features of resilience and machine learning", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:767064