TY - JOUR AU - Király, Roland AU - Király, Sándor AU - Palotai, M. TI - Investigating the usability of a new framework for creating, working and teaching artificial neural networks using augmented reality (AR) and virtual reality (VR) tools JF - EDUCATION AND INFORMATION TECHNOLOGIES J2 - EDUC INF TECHNOL VL - 2023 PY - 2023 SN - 1360-2357 DO - 10.1007/s10639-023-12349-5 UR - https://m2.mtmt.hu/api/publication/34623322 ID - 34623322 N1 - Export Date: 18 February 2024 Correspondence Address: Kiraly, R.; Department of Information Technology, Hungary; email: kiraly.roland@uni-eszterhazy.hu Correspondence Address: Kiraly, S.; Department of Information Technology, Hungary; email: kiraly.sandor@uni-eszterhazy.hu Correspondence Address: Palotai, M.; Department of Information Technology, Hungary; email: palotaimartinm@gmail.com AB - 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). LA - English DB - MTMT ER - TY - CHAP AU - Király, Roland AU - Király, Sándor AU - Palotai, Martin Marcell ED - Tick, József ED - Kokas, Károly ED - Holl, András TI - Neurális hálózatok oktatási alkalmazását támogató keretrendszer Virtual (VR) és Augmented Reality (AR) eszközökkel T2 - Új technológiákkal, új tartalmakkal a jövő digitális transzformációja felé PB - Hungarnet CY - Budapest SN - 9786158224314 PY - 2023 SP - 60 EP - 68 PG - 9 DO - 10.31915/NWS.2023.10 UR - https://m2.mtmt.hu/api/publication/34441893 ID - 34441893 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Király, Sándor AU - Balla, Tamás ED - Tick, József ED - Kokas, Károly ED - Holl, András TI - Flipped classroom az sqlsuli.hu-ban T2 - Új technológiákkal, új tartalmakkal a jövő digitális transzformációja felé PB - Hungarnet CY - Budapest SN - 9786158224314 PY - 2023 SP - 7 EP - 13 PG - 7 DO - 10.31915/NWS.2023.1 UR - https://m2.mtmt.hu/api/publication/34440487 ID - 34440487 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Király, Sándor AU - Balla, Tamás AU - Király, Roland TI - Learning SQL by practicing on popular movie databases JF - CENTRAL-EUROPEAN JOURNAL OF NEW TECHNOLOGIES IN RESEARCH EDUCATION AND PRACTICE J2 - CEJ-NETREP VL - 4 PY - 2022 IS - 1 SP - 16 EP - 24 PG - 9 SN - 2676-9425 DO - 10.36427/CEJNTREP.4.1.4465 UR - https://m2.mtmt.hu/api/publication/33180513 ID - 33180513 LA - English DB - MTMT ER - TY - JOUR AU - Balla, Tamás AU - Király, Sándor TI - A Discussion of Developing a Programming Education Portal JF - CENTRAL-EUROPEAN JOURNAL OF NEW TECHNOLOGIES IN RESEARCH EDUCATION AND PRACTICE J2 - CEJ-NETREP VL - 2 PY - 2020 IS - 2 SP - 1 EP - 14 PG - 14 SN - 2676-9425 DO - 10.36427/CEJNTREP.2.2 UR - https://m2.mtmt.hu/api/publication/31784760 ID - 31784760 LA - English DB - MTMT ER - TY - JOUR AU - Király, Sándor AU - Balla, Tamás TI - The effectiveness of a fully gamified programming course after combining with serious games JF - ACTA DIDACTICA NAPOCENSIA J2 - ACTA DID NAPOC VL - 13 PY - 2020 IS - 1 SP - 65 EP - 76 PG - 12 SN - 2065-1430 DO - 10.24193/adn.13.1.7 UR - https://m2.mtmt.hu/api/publication/31409198 ID - 31409198 LA - English DB - MTMT ER - TY - CONF AU - Balla, Tamás AU - Király, Sándor ED - Kovásznai, Gergely ED - Fazekas, István ED - Tómács, Tibor TI - Enhancing learning efficiency after analysing the users' results in a gamified learning portal for computer programming education T2 - Proceedings of the 11th International Conference on Applied Informatics (ICAI 2020) PB - CEUR Workshop Proceedings C1 - Eger T3 - CEUR Workshop Proceedings, ISSN 1613-0073 ; 2650. PY - 2020 SP - 23 EP - 23 PG - 1 UR - https://m2.mtmt.hu/api/publication/31366279 ID - 31366279 LA - English DB - MTMT ER - TY - CONF AU - Király, Sándor AU - Csutorás, Dániel ED - Kovásznai, Gergely ED - Fazekas, István ED - Tómács, Tibor TI - Smart TeamBoard: a Knowledge Sharing Progressive Web Application Supported by Efficient Convolutional Neural Networks T2 - Proceedings of the 11th International Conference on Applied Informatics (ICAI 2020) PB - CEUR Workshop Proceedings C1 - Eger T3 - CEUR Workshop Proceedings, ISSN 1613-0073 ; 2650. PY - 2020 SP - 2 EP - 2 PG - 2 UR - https://m2.mtmt.hu/api/publication/31366253 ID - 31366253 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Pap, Melinda AU - Király, Sándor AU - Molják, Sándor TI - Analysing the vegetation of energy plants by processing UAV images JF - ANNALES MATHEMATICAE ET INFORMATICAE J2 - ANN MATH INFORM VL - 52 PY - 2020 SP - 183 EP - 197 PG - 15 SN - 1787-5021 DO - 10.33039/ami.2020.01.001 UR - https://m2.mtmt.hu/api/publication/31170442 ID - 31170442 AB - 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. LA - English DB - MTMT ER - TY - JOUR AU - Balla, Tamás AU - Király, Sándor TI - Quality improvement of learning efficiency atkodolosuli.hu website JF - TEACHING MATHEMATICS AND COMPUTER SCIENCE J2 - TEACH MATH COMP SCI VL - 17 PY - 2019 IS - 2 SP - 246 SN - 1589-7389 DO - 10.5485/TMCS.2019.R030 UR - https://m2.mtmt.hu/api/publication/31373601 ID - 31373601 LA - English DB - MTMT ER -