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Zsolt Szalay
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2020 – today
- 2024
- [j16]Daniel Grimm
, Dávid Tollner, David Kraus
A numerical verification method for multi-class feed-forward neural networks. Expert Syst. Appl. 247: 123345 (2024) - [j15]Zsombor Petho
Quantifying Cyber Risks: The Impact of DoS Attacks on Vehicle Safety in V2X Networks. IEEE Trans. Intell. Transp. Syst. 25(11): 18591-18600 (2024) - [c14]András Rövid, Viktor Tihanyi, Márton Cserni, Mihály Csonthó, Ádám Domina, Viktor Remeli, Zsolt Vincze, Mátyás Szántó, Mátyás Szalai, Szabolcs Nagy, Zsolt Szalay:
Digital Twin and Cloud Based Remote Control of Vehicles. MOST 2024: 154-167 - 2023
- [j14]Zsolt Szalay
Critical Scenario Identification Concept: The Role of the Scenario-in-the-Loop Approach in Future Automotive Testing. IEEE Access 11: 82464-82476 (2023) - [c13]Árpád Somogyi, Tamás Tettamanti, Pál Varga, Zsolt Szalay, Dániel Baranyai, Tamas Lovas:
Digital Map Generation Workflow Demonstrated on ZalaZONE Automotive Proving Ground Elements. NOMS 2023: 1-6 - 2022
- [j13]Mihály Csonthó
Significance of Image Features in Camera-LiDAR Based Object Detection. IEEE Access 10: 61034-61045 (2022) - [j12]Árpád Török
New Aspects of Integrity Levels in Automotive Industry-Cybersecurity of Automated Vehicles. IEEE Trans. Intell. Transp. Syst. 23(1): 383-391 (2022) - [j11]Zsombor Petho
Safety risk focused analysis of V2V communication especially considering cyberattack sensitive network performance and vehicle dynamics factors. Veh. Commun. 37: 100514 (2022) - 2021
- [j10]Zsolt Szalay
Next Generation X-in-the-Loop Validation Methodology for Automated Vehicle Systems. IEEE Access 9: 35616-35632 (2021) - [j9]Szabolcs Duleba, Tamás Tettamanti
Ranking the Key Areas for Autonomous Proving Ground Development Using Pareto Analytic Hierarchy Process. IEEE Access 9: 51214-51230 (2021) - [j8]Henrietta Lengyel
A collection of easily deployable adversarial traffic sign stickers. Autom. 69(6): 511-523 (2021) - [j7]Zsombor Petho
A survey of new orientations in the field of vehicular cybersecurity, applying artificial intelligence based methods. Trans. Emerg. Telecommun. Technol. 32(10) (2021) - [j6]Maen Ghadi
A new methodology for analyzing vehicle network topologies for critical hacking. J. Ambient Intell. Humaniz. Comput. 12(7): 7923-7934 (2021) - [j5]Viktor Tihanyi
Motorway Measurement Campaign to Support R&D Activities in the Field of Automated Driving Technologies. Sensors 21(6): 2169 (2021) - [c12]Dániel Ficzere, Gábor Soós, Pál Varga, Zsolt Szalay:
Real-life V2X Measurement Results for 5G NSA Performance on a High-speed Motorway. IM 2021: 836-841 - 2020
- [j4]Henrietta Lengyel
Conflicts of Automated Driving With Conventional Traffic Infrastructure. IEEE Access 8: 163280-163297 (2020) - [j3]András Rövid, Viktor Remeli, Zsolt Szalay
Raw fusion of camera and sparse LiDAR for detecting distant objects. Autom. 68(5): 337-346 (2020) - [j2]Árpád Török
Modelling the effects of certain cyber-attack methods on urban autonomous transport systems, case study of Budapest. J. Ambient Intell. Humaniz. Comput. 11(4): 1629-1643 (2020) - [j1]Zsolt Szalay
5G-Enabled Autonomous Driving Demonstration with a V2X Scenario-in-the-Loop Approach. Sensors 20(24): 7344 (2020) - [c11]Árpád Fehér, Szilárd Aradi, Tamás Bécsi
Proving Ground Test of a DDPG-based Vehicle Trajectory Planner. ECC 2020: 332-337 - [c10]Ádám Bárdos
Implementation and experimental evaluation of a MIMO drifting controller on a test vehicle. IV 2020: 1472-1478 - [c9]Gábor Soós, Dániel Ficzere, Pál Varga, Zsolt Szalay:
Practical 5G KPI Measurement Results on a Non-Standalone Architecture. NOMS 2020: 1-5
2010 – 2019
- 2019
- [c8]Manuel Koschuch
Safety & Security in the Context of Autonomous Driving. ICCVE 2019: 1-7 - [c7]Zsolt Szalay
Proof of concept for Scenario-in-the-Loop (SciL) testing for autonomous vehicle technology. ICCVE 2019: 1-5 - [c6]Szilvia Lestyan, Gergely Ács, Gergely Biczók
Extracting Vehicle Sensor Signals from CAN Logs for Driver Re-identification. ICISSP 2019: 136-145 - [i2]Szilvia Lestyan, Gergely Ács, Gergely Biczók, Zsolt Szalay:
Extracting Vehicle Sensor Signals from CAN Logs for Driver Re-identification. CoRR abs/1902.08956 (2019) - 2018
- [c5]András Gazdag, Dóra Neubrandt, Levente Buttyán, Zsolt Szalay:
Detection of Injection Attacks in Compressed CAN Traffic Logs. ISSA/CSITS@ESORICS 2018: 111-124 - [c4]Zsolt Szalay, Zoltán Hamar, Peter Simon:
A Multi-layer Autonomous Vehicle and Simulation Validation Ecosystem Axis: ZalaZONE. IAS 2018: 954-963 - 2017
- [c3]András Gazdag, Levente Buttyán, Zsolt Szalay
Efficient lossless compression of CAN traffic logs. SoftCOM 2017: 1-6 - [i1]Zsolt Szalay, Domokos Esztergár-Kiss, Tamás Tettamanti, Péter Gáspár, István Varga:
RECAR: Hungarian Research Centre for Autonomous Road Vehicles is on the Way. ERCIM News 2017(109) (2017) - 2015
- [c2]László Lengyel, Péter Ekler, Tamas Ujj, Tamas Balogh, Hassan Charaf, Zsolt Szalay
ICT in road vehicles - The VehicleICT platform. MT-ITS 2015: 457-462 - [c1]Zsolt Szalay
ICT in road vehicles - Reliable vehicle sensor information from OBD versus CAN. MT-ITS 2015: 469-476
Coauthor Index
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