Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Márton Szemenyei"'
Publikováno v:
Cleaner Environmental Systems, Vol 13, Iss , Pp 100184- (2024)
The quality of community decisions about the key characteristics of urban services depends on the level of involvement of local stakeholder groups. The identification of the environmental, economic and social impacts of investments to improve urban s
Externí odkaz:
https://doaj.org/article/fbe3d70e159241cba6023764468828ea
Autor:
Márton Szemenyei, Mátyás Szántó
Publikováno v:
Applied Sciences, Vol 13, Iss 5, p 3090 (2023)
Neural network-based solutions have revolutionized the field of computer vision by achieving outstanding performance in a number of applications. Yet, while these deep learning models outclass previous methods, they still have significant shortcoming
Externí odkaz:
https://doaj.org/article/e9bc3817a40048c4a3a7925980a31c0d
Publikováno v:
Sensors, Vol 23, Iss 4, p 1874 (2023)
Driver fatigue reduces the safety of traditional driving and limits the widespread adoption of self-driving cars; hence, the monitoring and early detection of drivers’ drowsiness plays a key role in driving automation. When representing the drowsin
Externí odkaz:
https://doaj.org/article/c1a84121d5564151acebfd325b13c928
Publikováno v:
Sensors
Volume 23
Issue 4
Pages: 1874
Volume 23
Issue 4
Pages: 1874
Driver fatigue reduces the safety of traditional driving and limits the widespread adoption of self-driving cars; hence, the monitoring and early detection of drivers’ drowsiness plays a key role in driving automation. When representing the drowsin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::574ac9eb2785dea79cbc5c00e0ab5397
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783031234798
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::909d863797615016eeef93d4dbdd453f
https://doi.org/10.1007/978-3-031-23480-4_6
https://doi.org/10.1007/978-3-031-23480-4_6
Autor:
Márton Szemenyei, Patrik Reizinger
Publikováno v:
Journal of Artificial Intelligence and Soft Computing Research. 12:135-148
1Most reinforcement learning benchmarks – especially in multi-agent tasks – do not go beyond observations with simple noise; nonetheless, real scenarios induce more elaborate vision pipeline failures: false sightings, misclassifications or occlus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::816c189924dc60571a9dd0298b034774
https://doi.org/10.2478/jaiscr-2022-0009
https://doi.org/10.2478/jaiscr-2022-0009