Zobrazeno 1 - 10
of 374
pro vyhledávání: '"Carlo S Regazzoni"'
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 13 (2017)
Cognitive radio is a promising technology for frequency allocation to improve the spectrum utilization efficiency of licensed bands. However, in recent years, the attention of the researchers is focused on security issues that have to be faced by cog
Externí odkaz:
https://doaj.org/article/92e4d5977a614dac80ce54e5dd11911a
Autor:
Lucio Marcenaro, Damian Campo, Mahdyar Ravanbakhsh, Mohamad Baydoun, Carlo S. Regazzoni, Pablo Marin, David Martin
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 22:3372-3386
The technology for autonomous vehicles is close to replacing human drivers by artificial systems endowed with high-level decision-making capabilities. In this regard, systems must learn about the usual vehicle's behavior to predict imminent difficult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a016c52fe9779b31b834a5a7183a4a73
https://doi.org/10.1109/tits.2020.2984735
https://doi.org/10.1109/tits.2020.2984735
Publikováno v:
Proceedings of the IEEE. 108:971-975
Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4df1e517b8aee1b72f6e1dc90ee41e89
https://doi.org/10.1109/jproc.2020.2990784
https://doi.org/10.1109/jproc.2020.2990784
Publikováno v:
IEEE Transactions on Cognitive Communications and Networking. 6:1-5
We are delighted to introduce this special section of the IEEE Transactions on Cognitive Communications and Networking (TCCN), which aims at addressing the evolution of cognitive radio (CR) to intelligence radio and networks by exploring recent advan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c039fd78fd13d35d2c52521f4c37324
https://doi.org/10.1109/tccn.2020.2975440
https://doi.org/10.1109/tccn.2020.2975440
Autor:
Yingxu Wang, Bernard Widrow, Witold Pedrycz, Robert C. Berwick, Paolo Soda, Sam Kwong, Okyay Kaynak, Carlo S. Regazzoni, Christine Chan, Marina Gavrilova, Guoyin Wang
Publikováno v:
2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3736758df96e17849a0f6d293f2fbcf
https://doi.org/10.1109/iccicc53683.2021.9811324
https://doi.org/10.1109/iccicc53683.2021.9811324
Publikováno v:
2021 IEEE International Conference on Autonomous Systems (ICAS).
When performing anomaly detection on an autonomous vehicle’s sensory data, it is fundamental to infer the cause of the found anomalies. This paper proposes a method for learning prediction models and detecting anomalies by decomposing the evolution
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4cdd4927c2ba284afd4615273e3003ae
https://doi.org/10.1109/icas49788.2021.9551111
https://doi.org/10.1109/icas49788.2021.9551111
Autor:
Carlo S. Regazzoni
Publikováno v:
2021 IEEE International Conference on Autonomous Systems (ICAS).
Multisensor signal Data Fusion and Perception, including processing of signals are important cognitive functionalities that can be included in artificial systems to increase their level of autonomy. However, the techniques they rely on have been deve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::98372b41dc9fbd4c7602254a7d4f790f
https://doi.org/10.1109/icas49788.2021.9551132
https://doi.org/10.1109/icas49788.2021.9551132
Publikováno v:
2021 IEEE International Conference on Autonomous Systems (ICAS).
This paper proposes an adaptive method to enable imitation learning from expert demonstrations in a multi-agent context. The proposed system employs the inverse reinforcement learning method to a coupled Dynamic Bayesian Network to facilitate dynamic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::543c9f9919dc6d3fa719687f7e404d56
https://doi.org/10.1109/icas49788.2021.9551152
https://doi.org/10.1109/icas49788.2021.9551152
Autor:
Arumugam Nallanathan, Atm Shafiul Alam, Ali Krayani, Carlo S. Regazzoni, Lucio Marcenaro, Marco Calipari
Publikováno v:
WF-IoT
This paper proposes a novel Automatic Modulation Classification (AMC) method for CR-IoT based on learning multiple Generalized Dynamic Bayesian Networks (GDBN) as representations of various signals under different modulation schemes. The CR-IoT perfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f694b873e187e5a046bacee6ec90629
https://doi.org/10.1109/wf-iot51360.2021.9594936
https://doi.org/10.1109/wf-iot51360.2021.9594936
Anomaly detection constitutes a fundamental step in developing self-aware autonomous agents capable of continuously learning from new situations, as it enables to distinguish novel experiences from already encountered ones. This paper combines Dynami
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71f9778625c03df8980bab939c7ba3dc
https://hdl.handle.net/11567/1045183
https://hdl.handle.net/11567/1045183
