Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Ines Obradovic"'
Application of Deep Learning Architectures for Accurate Detection of Olive Tree Flowering Phenophase
Publikováno v:
Remote Sensing, Vol 12, Iss 13, p 2120 (2020)
The importance of monitoring and modelling the impact of climate change on crop phenology in a given ecosystem is ever-growing. For example, these procedures are useful when planning various processes that are important for plant protection. In order
Externí odkaz:
https://doaj.org/article/37d49807593c49e1819dd469a8a1b30a
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2021, Iss 1, Pp 1-18 (2021)
As the PHY/MAC-layer IR-HARQ and RLC-layer ARQ error recovery procedures, adopted in LTE, may impose additional delay when their code-block retransmissions occur, the arising question is whether these significantly contribute to IP and consequently R
Application of Deep Learning Architectures for Accurate Detection of Olive Tree Flowering Phenophase
Publikováno v:
Remote Sensing, Vol 12, Iss 2120, p 2120 (2020)
The importance of monitoring and modelling the impact of climate change on crop phenology in a given ecosystem is ever-growing. For example, these procedures are useful when planning various processes that are important for plant protection. In order
Publikováno v:
Naše more. 65:56-62
The maritime industry is a complex system that requires quick adaptation to changing conditions and in which decision-making needs to take into account a large number of parameters. As navigation systems become more advanced, there is a significant a
Publikováno v:
EuCNC
As the LTE PHY/MAC-layer IR HARQ and RLC-layer ARQ protocol, adopted in LTE, may create sudden ramping of the delay when retransmissions occur, the arising question is whether these significantly and dominantly contribute to the overall packet delay
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9aa6518eac61a0ce34dd94daf3165f71
https://doi.org/10.1109/eucnc.2019.8801978
https://doi.org/10.1109/eucnc.2019.8801978
Publikováno v:
Scopus-Elsevier
Fine-grained classification consists of learning and understanding the subtle details between visually similar classes, which is a difficult task even for a human expert trained in a corresponding scientific field. Similar performances can be achieve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5b5bec3f001a3dc9da3de1502e4321f9
https://www.bib.irb.hr/968081
https://www.bib.irb.hr/968081
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9783030215064
The automatic classification of maritime vessel type from low resolution images is a significant challenge and continues to attract increasing interest because of its importance to maritime surveillance. Convolutional neural networks are the method o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24327bb22504057e955a0a795f47cf13
https://doi.org/10.1007/978-3-030-21507-1_19
https://doi.org/10.1007/978-3-030-21507-1_19
Publikováno v:
SoftCOM
This paper describes implementation and evaluation of a method for automatic creation of concept map from unstructured text written in the Croatian language. The method combines statistical and data mining techniques with domain thesaurus and tools s
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2021, Iss 1, Pp 1-18 (2021)
Abstract As the PHY/MAC-layer IR-HARQ and RLC-layer ARQ error recovery procedures, adopted in LTE, may impose additional delay when their code-block retransmissions occur, the arising question is whether these significantly contribute to IP and conse
Externí odkaz:
https://doaj.org/article/fb92f21c96654eadbe62f1d50672be81
Publikováno v:
Naše More (Dubrovnik), Vol 65, Iss 1, Pp 56-62 (2018)
Maritime industry is a complex system that requires a quick adaptation to changing conditions and in which decision-making needs to take into account a large number of parameters. As navigation systems become more advanced, there is a significant amo
Externí odkaz:
https://doaj.org/article/0bc79485b25a47b5b4b4a135eda10bc0