@article{MTMT:34762087,
	title = {A kvadkopter szabályozási módjai},
	url = {https://m2.mtmt.hu/api/publication/34762087},
	author = {Kiss, Barnabás and Ballagi, Áron and Kuczmann, Miklós},
	journal-iso = {ELEKTROTECHNIKA},
	journal = {ELEKTROTECHNIKA},
	volume = {2024/1-2},
	unique-id = {34762087},
	issn = {0367-0708},
	year = {2024},
	pages = {8-12}
}

@article{MTMT:34689935,
	title = {Bus Driver Head Position Detection Using Capsule Networks Under Dynamic Driving Conditions},
	url = {https://m2.mtmt.hu/api/publication/34689935},
	author = {Hollósi, János and Ballagi, Áron and Kovács, Gábor and Fischer, Szabolcs and Nagy, Viktor},
	doi = {10.3390/computers13030066},
	journal-iso = {COMPUTERS},
	journal = {COMPUTERS},
	volume = {13},
	unique-id = {34689935},
	year = {2024},
	eissn = {2073-431X},
	orcid-numbers = {Fischer, Szabolcs/0000-0001-7298-9960}
}

@inproceedings{MTMT:34474925,
	title = {Questions Regarding the Applicability of a LiDAR-Based SLAM Method},
	url = {https://m2.mtmt.hu/api/publication/34474925},
	author = {Krecht, Rudolf and Ballagi, Áron},
	booktitle = {2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)},
	doi = {10.1109/ICECCME57830.2023.10252731},
	unique-id = {34474925},
	year = {2023},
	pages = {1-6},
	orcid-numbers = {Krecht, Rudolf/0000-0002-8927-8783}
}

@inproceedings{MTMT:34473012,
	title = {Terrain Depth Estimation for Improved Inertial Data Prediction in Autonomous Navigation Systems},
	url = {https://m2.mtmt.hu/api/publication/34473012},
	author = {Markó, Norbert and Szirányi, Tamás and Ballagi, Áron},
	booktitle = {2023 IEEE International Automated Vehicle Validation Conference (IAVVC)},
	doi = {10.1109/IAVVC57316.2023.10328139},
	unique-id = {34473012},
	year = {2023},
	pages = {1-6},
	orcid-numbers = {Szirányi, Tamás/0000-0003-2989-0214}
}

@CONFERENCE{MTMT:34125043,
	title = {Emberi arc detektálásának vizsgálata kapszula hálózatok alkalmazásával},
	url = {https://m2.mtmt.hu/api/publication/34125043},
	author = {Hollósi, János and Ballagi, Áron and Pozna, Claudiu Radu},
	booktitle = {Mesterséges intelligencia rendszerek alkalmazása a mobilitásban konferencia},
	unique-id = {34125043},
	year = {2023}
}

@inproceedings{MTMT:34125032,
	title = {Capsule Network based 3D Object Orientation Estimation},
	url = {https://m2.mtmt.hu/api/publication/34125032},
	author = {Hollósi, János and Ballagi, Áron and Pozna, Claudiu Radu},
	booktitle = {2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)},
	doi = {10.1109/ICECCME57830.2023.10252762},
	unique-id = {34125032},
	year = {2023}
}

@article{MTMT:34112953,
	title = {Simplified Routing Mechanism for Capsule Networks},
	url = {https://m2.mtmt.hu/api/publication/34112953},
	author = {Hollósi, János and Ballagi, Áron and Pozna, Claudiu Radu},
	doi = {10.3390/a16070336},
	journal-iso = {ALGORITHMS},
	journal = {ALGORITHMS},
	volume = {16},
	unique-id = {34112953},
	abstract = {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.},
	year = {2023},
	eissn = {1999-4893},
	pages = {336}
}

@article{MTMT:34092526,
	title = {Face detection using a capsule network for driver monitoring application},
	url = {https://m2.mtmt.hu/api/publication/34092526},
	author = {Hollósi, János and Ballagi, Áron and Kovács, Gábor and Fischer, Szabolcs and Nagy, Viktor},
	doi = {10.3390/computers12080161},
	journal-iso = {COMPUTERS},
	journal = {COMPUTERS},
	volume = {12},
	unique-id = {34092526},
	year = {2023},
	eissn = {2073-431X},
	orcid-numbers = {Fischer, Szabolcs/0000-0001-7298-9960}
}

@article{MTMT:34058348,
	title = {Implementation of Trajectory Planning Algorithms for Track Serving Mobile Robot in ROS 2 Ecosystem},
	url = {https://m2.mtmt.hu/api/publication/34058348},
	author = {Boros, Norbert and Kallós, Gábor and Ballagi, Áron},
	doi = {10.17559/TV-20220823131848},
	journal-iso = {TEH VJESN},
	journal = {TEHNICKI VJESNIK-TECHNICAL GAZETTE},
	volume = {30},
	unique-id = {34058348},
	issn = {1330-3651},
	year = {2023},
	eissn = {1848-6339},
	pages = {1020-1028}
}

@article{MTMT:33967466,
	title = {Towards the resilience quantification of (military) unmanned ground vehicles},
	url = {https://m2.mtmt.hu/api/publication/33967466},
	author = {Krecht, Rudolf and Suta, Alex and Tóth, Árpád and Ballagi, Áron},
	doi = {10.1016/j.clet.2023.100644},
	journal-iso = {CLEANER ENGINEERING AND TECHNOLOGY},
	journal = {CLEANER ENGINEERING AND TECHNOLOGY},
	volume = {14},
	unique-id = {33967466},
	year = {2023},
	eissn = {2666-7908},
	orcid-numbers = {Krecht, Rudolf/0000-0002-8927-8783}
}