Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Petra Bevandić"'
Publikováno v:
Sensors, Vol 24, Iss 4, p 1248 (2024)
Standard machine learning is unable to accommodate inputs which do not belong to the training distribution. The resulting models often give rise to confident incorrect predictions which may lead to devastating consequences. This problem is especially
Externí odkaz:
https://doaj.org/article/1e0f819a0d6d46c58b7b716cc7615056
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 21:336-345
Visual cues can be used alongside GPS positioning and digital maps to improve understanding of vehicle environment in fleet management systems. Such systems are limited both in terms of bandwidth and storage space, so minimizing the size of transmitt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47c559bd44bdf745c821d6beb71902cf
https://doi.org/10.1109/tits.2019.2891995
https://doi.org/10.1109/tits.2019.2891995
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031198052
Anomaly detection can be conceived either through generative modelling of regular training data or by discriminating with respect to negative training data. These two approaches exhibit different failure modes. Consequently, hybrid algorithms present
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9335528c0b767525b3e3426ee1fa70a7
https://www.bib.irb.hr/1236654
https://www.bib.irb.hr/1236654
Publikováno v:
VISIGRAPP (4: VISAPP)
Today's deep models are often unable to detect inputs which do not belong to the training distribution. This gives rise to confident incorrect predictions which could lead to devastating consequences in many important application fields such as healt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce915c08273a6aa6aea61d37c32085a0
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030336752
GCPR
GCPR
Recent success on realistic road driving datasets has increased interest in exploring robust performance in real-world applications. One of the major unsolved problems is to identify image content which can not be reliably recognized with a given inf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::576bb2b2b275c771096f436bcc61a47c
Publikováno v:
CVPR
Recent success of semantic segmentation approaches on demanding road driving datasets has spurred interest in many related application fields. Many of these applications involve real-time prediction on mobile platforms such as cars, drones and variou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::833a1597ad392fa3d432bdf515912c67