TY - JOUR AU - Kiss, Barnabás AU - Ballagi, Áron AU - Kuczmann, Miklós TI - A kvadkopter szabályozási módjai JF - ELEKTROTECHNIKA J2 - ELEKTROTECHNIKA VL - 2024/1-2 PY - 2024 IS - 117. évfolyam SP - 8 EP - 12 PG - 5 SN - 0367-0708 UR - https://m2.mtmt.hu/api/publication/34762087 ID - 34762087 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Hollósi, János AU - Ballagi, Áron AU - Kovács, Gábor AU - Fischer, Szabolcs AU - Nagy, Viktor TI - Bus Driver Head Position Detection Using Capsule Networks Under Dynamic Driving Conditions JF - COMPUTERS J2 - COMPUTERS VL - 13 PY - 2024 IS - 3 SN - 2073-431X DO - 10.3390/computers13030066 UR - https://m2.mtmt.hu/api/publication/34689935 ID - 34689935 LA - English DB - MTMT ER - TY - CHAP AU - Krecht, Rudolf AU - Ballagi, Áron TI - Questions Regarding the Applicability of a LiDAR-Based SLAM Method T2 - 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) PB - IEEE CY - Piscataway (NJ) SN - 9798350322972 PY - 2023 SP - 1 EP - 6 PG - 6 DO - 10.1109/ICECCME57830.2023.10252731 UR - https://m2.mtmt.hu/api/publication/34474925 ID - 34474925 LA - English DB - MTMT ER - TY - CHAP AU - Markó, Norbert AU - Szirányi, Tamás AU - Ballagi, Áron TI - Terrain Depth Estimation for Improved Inertial Data Prediction in Autonomous Navigation Systems T2 - 2023 IEEE International Automated Vehicle Validation Conference (IAVVC) PB - IEEE CY - Piscataway (NJ) SN - 9798350322538 PY - 2023 SP - 1 EP - 6 PG - 6 DO - 10.1109/IAVVC57316.2023.10328139 UR - https://m2.mtmt.hu/api/publication/34473012 ID - 34473012 LA - English DB - MTMT ER - TY - CONF AU - Hollósi, János AU - Ballagi, Áron AU - Pozna, Claudiu Radu TI - Emberi arc detektálásának vizsgálata kapszula hálózatok alkalmazásával T2 - Mesterséges intelligencia rendszerek alkalmazása a mobilitásban konferencia PY - 2023 UR - https://m2.mtmt.hu/api/publication/34125043 ID - 34125043 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Hollósi, János AU - Ballagi, Áron AU - Pozna, Claudiu Radu TI - Capsule Network based 3D Object Orientation Estimation T2 - 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) PB - IEEE CY - Piscataway (NJ) SN - 9798350322972 PY - 2023 DO - 10.1109/ICECCME57830.2023.10252762 UR - https://m2.mtmt.hu/api/publication/34125032 ID - 34125032 LA - English DB - MTMT ER - TY - JOUR AU - Hollósi, János AU - Ballagi, Áron AU - Pozna, Claudiu Radu TI - Simplified Routing Mechanism for Capsule Networks JF - ALGORITHMS J2 - ALGORITHMS VL - 16 PY - 2023 IS - 7 SP - 336 SN - 1999-4893 DO - 10.3390/a16070336 UR - https://m2.mtmt.hu/api/publication/34112953 ID - 34112953 AB - Classifying digital images using neural networks is one of the most fundamental tasks within the field of artificial intelligence. For a long time, convolutional neural networks have proven to be the most efficient solution for processing visual data, such as classification, detection, or segmentation. The efficient operation of convolutional neural networks requires the use of data augmentation and a high number of feature maps to embed object transformations. Especially for large datasets, this approach is not very efficient. In 2017, Geoffrey Hinton and his research team introduced the theory of capsule networks. Capsule networks offer a solution to the problems of convolutional neural networks. In this approach, sufficient efficiency can be achieved without large-scale data augmentation. However, the training time for Hinton’s capsule network is much longer than for convolutional neural networks. We have examined the capsule networks and propose a modification in the routing mechanism to speed up the algorithm. This could reduce the training time of capsule networks by almost half in some cases. Moreover, our solution achieves performance improvements in the field of image classification. LA - English DB - MTMT ER - TY - JOUR AU - Hollósi, János AU - Ballagi, Áron AU - Kovács, Gábor AU - Fischer, Szabolcs AU - Nagy, Viktor TI - Face detection using a capsule network for driver monitoring application JF - COMPUTERS J2 - COMPUTERS VL - 12 PY - 2023 IS - 8 PG - 16 SN - 2073-431X DO - 10.3390/computers12080161 UR - https://m2.mtmt.hu/api/publication/34092526 ID - 34092526 LA - English DB - MTMT ER - TY - JOUR AU - Boros, Norbert AU - Kallós, Gábor AU - Ballagi, Áron TI - Implementation of Trajectory Planning Algorithms for Track Serving Mobile Robot in ROS 2 Ecosystem JF - TEHNICKI VJESNIK-TECHNICAL GAZETTE J2 - TEH VJESN VL - 30 PY - 2023 IS - 4 SP - 1020 EP - 1028 PG - 9 SN - 1330-3651 DO - 10.17559/TV-20220823131848 UR - https://m2.mtmt.hu/api/publication/34058348 ID - 34058348 LA - English DB - MTMT ER - TY - JOUR AU - Krecht, Rudolf AU - Suta, Alex AU - Tóth, Árpád AU - Ballagi, Áron TI - Towards the resilience quantification of (military) unmanned ground vehicles JF - CLEANER ENGINEERING AND TECHNOLOGY J2 - CLEANER ENGINEERING AND TECHNOLOGY VL - 14 PY - 2023 SN - 2666-7908 DO - 10.1016/j.clet.2023.100644 UR - https://m2.mtmt.hu/api/publication/33967466 ID - 33967466 N1 - Export Date: 16 October 2023 Correspondence Address: Krecht, R.; Széchenyi István University, Egyetem Sq. 1, IS-201, Hungary; email: krecht.rudolf@ga.sze.hu Funding details: Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, NKFIA Funding details: Széchenyi István Egyetem, SZE, TKP2021-NVA-23, ÚNKP-22-3-I-SZE-39 Funding text 1: The research was supported by the ÚNKP-22-3-I-SZE-39 New National Excellence Program of the Ministry for Culture and Innovation of Hungary from the source of the National Research, Development and Innovation Fund . Funding text 2: The research presented in this paper was funded by the “ Thematic Excellence Programme 2021 (TKP 2021) – National Defence, National Security Subprogramme – Research on military systems resilience at Széchenyi István University ( TKP2021-NVA-23 )” project. LA - English DB - MTMT ER -