@article{MTMT:34623322,
	title = {Investigating the usability of a new framework for creating, working and teaching artificial neural networks using augmented reality (AR) and virtual reality (VR) tools},
	url = {https://m2.mtmt.hu/api/publication/34623322},
	author = {Király, Roland and Király, Sándor and Palotai, M.},
	doi = {10.1007/s10639-023-12349-5},
	journal-iso = {EDUC INF TECHNOL},
	journal = {EDUCATION AND INFORMATION TECHNOLOGIES},
	volume = {2023},
	unique-id = {34623322},
	issn = {1360-2357},
	abstract = {Deep learning is a very popular topic in computer sciences courses despite the fact that it is often challenging for beginners to take their first step due to the complexity of understanding and applying Artificial Neural Networks (ANN). Thus, the need to both understand and use neural networks is appearing at an ever-increasing rate across all computer science courses. Our objectives in this project were to create a framework for creating and training neural networks for solving different problems real-life problems and for research and education, as well as to investigate the usability of our framework. To provide an easy to use framework, this research recruited five instructors who have taught ANNs at two universities. We asked thirty-one students who have previously studied neural networks to fill out an online survey about what were "the major difficulties in learning NNs" and the "key requirements in a Visual Learning Tool including the most desired features of a visualization tool for explaining NNs" they would have used during the course. We also conducted an observational study to investigate how our students would use this system to learn about ANNs. The visual presentation of ANNs created in our framework can be represented in an Augmented Reality (AR) and Virtual Reality (VR) environment thus allowing us to use a virtual space to display and manage networks. An evaluation of the effect of the AR/VR experience through a formative test and survey showed that the majority of students had a positive response to the engaging and interactive features of our framework (RKNet). © 2023, The Author(s).},
	keywords = {VISUALIZATION; education; Virtual reality; artificial neural network; Augmented reality},
	year = {2023},
	eissn = {1573-7608}
}

@inproceedings{MTMT:34441893,
	title = {Neurális hálózatok oktatási alkalmazását támogató keretrendszer Virtual (VR) és Augmented Reality (AR) eszközökkel},
	url = {https://m2.mtmt.hu/api/publication/34441893},
	author = {Király, Roland and Király, Sándor and Palotai, Martin Marcell},
	booktitle = {Új technológiákkal, új tartalmakkal a jövő digitális transzformációja felé},
	doi = {10.31915/NWS.2023.10},
	unique-id = {34441893},
	year = {2023},
	pages = {60-68}
}

@inproceedings{MTMT:34440487,
	title = {Flipped classroom az sqlsuli.hu-ban},
	url = {https://m2.mtmt.hu/api/publication/34440487},
	author = {Király, Sándor and Balla, Tamás},
	booktitle = {Új technológiákkal, új tartalmakkal a jövő digitális transzformációja felé},
	doi = {10.31915/NWS.2023.1},
	unique-id = {34440487},
	year = {2023},
	pages = {7-13}
}

@article{MTMT:33180513,
	title = {Learning SQL by practicing on popular movie databases},
	url = {https://m2.mtmt.hu/api/publication/33180513},
	author = {Király, Sándor and Balla, Tamás and Király, Roland},
	doi = {10.36427/CEJNTREP.4.1.4465},
	journal-iso = {CEJ-NETREP},
	journal = {CENTRAL-EUROPEAN JOURNAL OF NEW TECHNOLOGIES IN RESEARCH EDUCATION AND PRACTICE},
	volume = {4},
	unique-id = {33180513},
	year = {2022},
	eissn = {2676-9425},
	pages = {16-24}
}

@article{MTMT:31784760,
	title = {A Discussion of Developing a Programming Education Portal},
	url = {https://m2.mtmt.hu/api/publication/31784760},
	author = {Balla, Tamás and Király, Sándor},
	doi = {10.36427/CEJNTREP.2.2},
	journal-iso = {CEJ-NETREP},
	journal = {CENTRAL-EUROPEAN JOURNAL OF NEW TECHNOLOGIES IN RESEARCH EDUCATION AND PRACTICE},
	volume = {2},
	unique-id = {31784760},
	year = {2020},
	eissn = {2676-9425},
	pages = {1-14}
}

@article{MTMT:31409198,
	title = {The effectiveness of a fully gamified programming course after combining with serious games},
	url = {https://m2.mtmt.hu/api/publication/31409198},
	author = {Király, Sándor and Balla, Tamás},
	doi = {10.24193/adn.13.1.7},
	journal-iso = {ACTA DID NAPOC},
	journal = {ACTA DIDACTICA NAPOCENSIA},
	volume = {13},
	unique-id = {31409198},
	issn = {2065-1430},
	year = {2020},
	pages = {65-76}
}

@CONFERENCE{MTMT:31366279,
	title = {Enhancing learning efficiency after analysing the users' results in a gamified learning portal for computer programming education},
	url = {https://m2.mtmt.hu/api/publication/31366279},
	author = {Balla, Tamás and Király, Sándor},
	booktitle = {Proceedings of the 11th International Conference on Applied Informatics (ICAI 2020)},
	unique-id = {31366279},
	year = {2020},
	pages = {23-23}
}

@CONFERENCE{MTMT:31366253,
	title = {Smart TeamBoard: a Knowledge Sharing Progressive Web Application Supported by Efficient Convolutional Neural Networks},
	url = {https://m2.mtmt.hu/api/publication/31366253},
	author = {Király, Sándor and Csutorás, Dániel},
	booktitle = {Proceedings of the 11th International Conference on Applied Informatics (ICAI 2020)},
	unique-id = {31366253},
	year = {2020},
	pages = {2-2}
}

@article{MTMT:31170442,
	title = {Analysing the vegetation of energy plants by processing UAV images},
	url = {https://m2.mtmt.hu/api/publication/31170442},
	author = {Pap, Melinda and Király, Sándor and Molják, Sándor},
	doi = {10.33039/ami.2020.01.001},
	journal-iso = {ANN MATH INFORM},
	journal = {ANNALES MATHEMATICAE ET INFORMATICAE},
	volume = {52},
	unique-id = {31170442},
	issn = {1787-5021},
	abstract = {Bioenergy plants are widely used as a form of renewable energy. It is important to monitor the vegetation and accurately estimate the yield before harvest in order to maximize the profit and reduce the costs of production. The automatic tracking of plant development by traditional methods is quite difficult and labor intensive. Nowadays, the application of Unmanned Aerial Vehicles (UAV) became more and more popular in precision agriculture. De-tailed, precise, three-dimensional (3D) representations of energy forestry are required as a prior condition for an accurate assessment of crop growth. Using a small UAV equipped with a multispectral camera, we collected imagery of 1051 pictures of a study area in Kompolt, Hungary, then the Pix4D software was used to create a 3D model of the forest canopy. Remotely sensed data was processed with the aid of Pix4Dmapper to create the orthophotos and the digital surface model. The calculated Normalized Difference Vegetation Index (NDVI) values were also calculated. The aim of this case study was to do the first step towards yield estimation, and segment the created or-thophoto, based on tree species. This is required, since different type of trees have different characteristics, thus, their yield calculations may differ. How-ever, the trees in the study area are versatile, there are also hybrids of the same species present. This paper presents the results of several segmentation algorithms, such as those that the widely used eCognition provides and other Matlab implementations of segmentation algorithms. © 2020, Eszterhazy Karoly College. All rights reserved.},
	keywords = {Segmentation; Photogrammetry; NDVI; 3D reconstruction},
	year = {2020},
	eissn = {1787-6117},
	pages = {183-197}
}

@article{MTMT:31373601,
	title = {Quality improvement of learning efficiency atkodolosuli.hu website},
	url = {https://m2.mtmt.hu/api/publication/31373601},
	author = {Balla, Tamás and Király, Sándor},
	doi = {10.5485/TMCS.2019.R030},
	journal-iso = {TEACH MATH COMP SCI},
	journal = {TEACHING MATHEMATICS AND COMPUTER SCIENCE},
	volume = {17},
	unique-id = {31373601},
	issn = {1589-7389},
	year = {2019},
	eissn = {2676-8364},
	pages = {246}
}