UMĚLÁ INTELIGENCE V AUTOMOTIVE / David et al.
[3.14] KOMORSKA, I., WOCZYSKI, Z., BORCZUCH, A. Fault diagnostics in air intake system of combustion engine using virtual sensors. Diagnostyka . 19 (2018). pp. 25–32. https://doi.org/10.29354/diag/80972. [3.15] ARSIE, I., CRICCHIO, A., DE CESARE, M., LAZZARINI, F., PIANESE, C., SORRENTINO, M. Neural network models for virtual sensing of NOx emissions in automotive diesel engines with least square-based adaptation. Control Engineering Practice . 61, 2017. pp. 11–20. https://doi.org/10.1016/j. conengprac.2017.01.005. [3.16] BAHL, S., SINGH, S., GOYAL, P., BAGHA, A.K. Experimental investigati ons on brass material and pin-fin based heat transfer system and its modeling by using adaptive neuro-fuzzy inference systém. Materials Today Proceedings . 45, 2021. pp. 5323–5327. https://doi.org/10.1016/j.matpr.2021.01.910. [3.17] AROMAA, S., VÄÄTÄNEN, A., AALTONEN, I., GORIACHEV, V., HELIN, K., KARJALAINEN, J. Awareness of the real-world environment when using augmented reality head-mounted display. Applied Ergonomics. 88, 2020. 103145. https://doi.org/10.1016/j.apergo.2020.103145. [3.18] LIU, S., LI, Y., ZHOU, P., LI, X., RONG, N., HUANG, S., LU, W., SU, Y. A multi-plane optical see-through head mounted display design for augmented reality applications. Journal of the Society for Information Display . 24 (4), 2016. pp. 246–251. https://doi.org/10.1002/jsid.435. [3.19] FAZAL, N., HALEEM, A., BAHL, S., JAVAID, M., NANDAN, D. Digi tal Management Systems in Manufacturing Using Industry 5.0 Technologies, in: P. Verma, O. D. Samuel, T. N. Verma, G. Dwivedi (Eds.). Advancement in Materials, Manufacturing and Energy Engineering. Vol. II , Springer, Singapore, 2022: pp. 221–234. https://doi.org/10.1007/978-981-16-8341-1_18. [3.20] NASSIF, A.B., SHAHIN, I., ATTILI, I., AZZEH, M., SHAALAN, K. Speech Recognition Using Deep Neural Networks: A Systematic Review, IEEE Access . 7, 2019. pp. 19143–19165. https://doi.org/10.1109/ACCESS.2019.2896880. [3.21] PARK, D. S., CHAN, W., ZHANG, Y., CHIU, C. C., ZOPH, B., CUBUK, E. D., LE, Q.V. SpecAugment: A simple data augmentation method for automatic speech recognition. Processing Annual Conference of the International Speech Communication Association, INTERSPEECH 2019 . 2019. pp. 2613–2617. https:// doi.org/10.21437/Interspeech.2019-2680. [3.22] HAMID, U.Z.A., SAITO, Y., ZAMZURI, H., RAHMAN, M.A.A., RAK SINCHAROENSAK, P. A review on threat assessment, path planning and path tracking strategies for collision avoidance systems of autonomous vehicles. International Journal of Vehicle Autonomous Systems . 14, 2018. pp. 134–169. https://doi.org/10.1504/IJVAS.2018.096154. [3.23] DRUML, N., MACHER, G., STOLZ, M., ARMENGAUD, E., WATZENIG, D., STEGER, C., HERNDL, T., ECKEL, A., RYABOKON, A., HOESS, A., KU MAR, S., DIMITRAKOPOULOS, G., ROEDIG, H. PRYSTINE – PRogram mable sYSTems for INtelligence in AutomobilEs, in: 2018 21st Euromicro Con-
137
Made with FlippingBook - Share PDF online