
Publications
Hanczár, G., Stippinger, M., Hanak, D., Kurbucz, T. M., Torteli, M. O., Chripko, A. & Somogyvari, Z (2023). Feature space reduction method for ultrahigh-dimensional, multiclass data: random forest-based multiround screening (RFMS). Machine Learning: Science and Technology, 4, 045012. https://dx.doi.org/10.1088/2632-2153/ad020e
Hanczár, G., Griechisch, E., Ovád, N., Törteli, O. M., Tóth, G., Hanák, D., Vértes, B., Horváth, A., & Kamondi, A. (2022). Detection of mild cognitive impairment based on mouse movement data of trail making test. Informatics in Medicine Unlocked, 35, 101120. https://doi.org/10.1016/j.imu.2022.101120
Hanczár, G., Griechisch, E., Molnár, Á., & Tóth, G. (2022). Motor Movement Data Collection from Older People with Tablets and Digital Pen-Based Input Devices. In: Carmona-Duarte, C., Diaz, M., Ferrer, M.A., Morales, A. (eds) Intertwining Graphonomics with Human Movements. IGS 2022. Lecture Notes in Computer Science, vol 13424. Springer, Cham. https://doi.org/10.1007/978-3-031-19745-1_18
Stippinger, M., Hanák, D., Kurbucz, M. T., Hanczár, G., Törteli, O. M., & Somogyvári, Z. (2023). BiometricBlender: Ultra-high dimensional, multi-class synthetic data generator to imitate biometric feature space. SoftwareX, 22, 101366. https://doi.org/10.1016/j.softx.2023.101366
Griechisch, E., Ward, J. R., & Hanczár, G. (2019). Anomalies in measuring speed and other dynamic properties with touchscreens and tablets. 2019 International Conference of the Biometrics Special Interest Group (BIOSIG), Darmstadt, Germany, pp. 1-6. https://ieeexplore.ieee.org/document/8897249