Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Cristian PEÑARANDA"'
Publikováno v:
Sensors, Vol 24, Iss 14, p 4649 (2024)
GPUs are commonly used to accelerate the execution of applications in domains such as deep learning. Deep learning applications are applied to an increasing variety of scenarios, with edge computing being one of them. However, edge devices present se
Externí odkaz:
https://doaj.org/article/10fb7ec42746495a84d943fb1d108263
Publikováno v:
Advances in Distributed Computing and Artificial Intelligence Journal, Vol 5, Iss 2, Pp 67-87 (2016)
This paper presents a proposal for a Smart Transport System which is an application that facilitates the interconnection between people (citizens, tourists) and transport providers (Bus, metro, trains, trams), defining the services that everyone can
Externí odkaz:
https://doaj.org/article/dd48a8989e8a4b64b662669833b118ee
Publikováno v:
Concurrency and Computation: Practice and Experience.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12e4fbefd47f1a1bffc6cdb60b6629bd
https://doi.org/10.1002/cpe.7328
https://doi.org/10.1002/cpe.7328
Publikováno v:
Workshop Proceedings of the 51st International Conference on Parallel Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd2e19f431e2d5a82eb83f9c503018ff
https://doi.org/10.1145/3547276.3548628
https://doi.org/10.1145/3547276.3548628
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031154706
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eea0ee60445b691bbf2f4413ccf68f94
https://doi.org/10.1007/978-3-031-15471-3_21
https://doi.org/10.1007/978-3-031-15471-3_21
Publikováno v:
IEEE Access, Vol 12, Pp 32706-32723 (2024)
Compression algorithms are widely used to reduce data size and improve application performance. Nevertheless, data compression has a computational cost which can limit its use. GPUs could be leveraged to reduce compression time. However, existing GPU
Externí odkaz:
https://doaj.org/article/51060b635ac045e0aa8ff32abaf67eff
Publikováno v:
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
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[EN] The main goal of this paper is to provide an approach to solve the problem of localization in mobile robots using multi-agent systems. Usually, the robot localization problem is solved in static environments by the addition of the needed sensors
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b9aeb56e7d3416ba92512606a2c7fea
http://hdl.handle.net/10251/126042
http://hdl.handle.net/10251/126042
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319596495
HAIS
HAIS
This paper provides a way to solve the problem of localization in mobile robots using a MAS approach. Typically, the robot localization has been resolved in static environments by adding sensors that help the robot, but this is not useful in dynamic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac7a99673e6f395f9df85dc9a14d668b
https://doi.org/10.1007/978-3-319-59650-1_40
https://doi.org/10.1007/978-3-319-59650-1_40
Publikováno v:
GREDOS. Repositorio Institucional de la Universidad de Salamanca
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Advances in Distributed Computing and Artificial Intelligence Journal, Vol 5, Iss 2, Pp 67-87 (2016)
instname
Advances in Distributed Computing and Artificial Intelligence Journal, Vol 5, Iss 2, Pp 67-87 (2016)
This paper presents a proposal for a Smart Transport System which is an application that facilitates the interconnection between people (citizens, tourists) and transport providers (Bus, metro, trains, trams), defining the services that everyone can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2eb97e5bcfb588296c215828d6a8dd3c
http://hdl.handle.net/10366/131911
http://hdl.handle.net/10366/131911
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319320335
HAIS
HAIS
Most of existing applications for locating and retrieving information are currently oriented towards offering personalized recommendations using well-known recommender techniques as content-based or collaborative filtering. Nevertheless, automatic in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7db107feb9b07c1bd7a295c0ff965ff7
https://doi.org/10.1007/978-3-319-32034-2_17
https://doi.org/10.1007/978-3-319-32034-2_17