Matches in SemOpenAlex for { <https://semopenalex.org/work/W2024365188> ?p ?o ?g. }
Showing items 1 to 92 of
92
with 100 items per page.
- W2024365188 endingPage "189" @default.
- W2024365188 startingPage "173" @default.
- W2024365188 abstract "In this paper we present a sound-source model for localising and tracking an acoustic source of interest along the azimuth plane in acoustically cluttered environments, for a mobile service robot. The model we present is a hybrid architecture using cross-correlation and recurrent neural networks to develop a robotic model accurate and robust enough to perform within an acoustically cluttered environment. This model has been developed with considerations of both processing power and physical robot size, allowing for this model to be deployed on to a wide variety of robotic systems where power consumption and size is a limitation. The development of the system we present has its inspiration taken from the central auditory system (CAS) of the mammalian brain. In this paper we describe experimental results of the proposed model including the experimental methodology for testing sound-source localisation systems. The results of the system are shown in both restricted test environments and in real-world conditions. This paper shows how a hybrid architecture using band pass filtering, cross-correlation and recurrent neural networks can be used to develop a robust, accurate and fast sound-source localisation model for a mobile robot." @default.
- W2024365188 created "2016-06-24" @default.
- W2024365188 creator A5016500874 @default.
- W2024365188 creator A5028839466 @default.
- W2024365188 creator A5033486668 @default.
- W2024365188 date "2009-03-01" @default.
- W2024365188 modified "2023-09-24" @default.
- W2024365188 title "Robotic sound-source localisation architecture using cross-correlation and recurrent neural networks" @default.
- W2024365188 cites W1966371537 @default.
- W2024365188 cites W1982431017 @default.
- W2024365188 cites W1993108030 @default.
- W2024365188 cites W1997027186 @default.
- W2024365188 cites W2012211082 @default.
- W2024365188 cites W2013710850 @default.
- W2024365188 cites W2023881054 @default.
- W2024365188 cites W2027024812 @default.
- W2024365188 cites W2033990903 @default.
- W2024365188 cites W2035040018 @default.
- W2024365188 cites W2051373563 @default.
- W2024365188 cites W2051676521 @default.
- W2024365188 cites W2055048333 @default.
- W2024365188 cites W2073355075 @default.
- W2024365188 cites W2078528333 @default.
- W2024365188 cites W2085770053 @default.
- W2024365188 cites W2101345274 @default.
- W2024365188 cites W2104422351 @default.
- W2024365188 cites W2110485445 @default.
- W2024365188 cites W2119188423 @default.
- W2024365188 cites W2140143700 @default.
- W2024365188 cites W2151399103 @default.
- W2024365188 cites W2152809449 @default.
- W2024365188 cites W2416573875 @default.
- W2024365188 doi "https://doi.org/10.1016/j.neunet.2009.01.013" @default.
- W2024365188 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/19233613" @default.
- W2024365188 hasPublicationYear "2009" @default.
- W2024365188 type Work @default.
- W2024365188 sameAs 2024365188 @default.
- W2024365188 citedByCount "42" @default.
- W2024365188 countsByYear W20243651882012 @default.
- W2024365188 countsByYear W20243651882013 @default.
- W2024365188 countsByYear W20243651882014 @default.
- W2024365188 countsByYear W20243651882015 @default.
- W2024365188 countsByYear W20243651882016 @default.
- W2024365188 countsByYear W20243651882017 @default.
- W2024365188 countsByYear W20243651882018 @default.
- W2024365188 countsByYear W20243651882020 @default.
- W2024365188 countsByYear W20243651882021 @default.
- W2024365188 countsByYear W20243651882022 @default.
- W2024365188 crossrefType "journal-article" @default.
- W2024365188 hasAuthorship W2024365188A5016500874 @default.
- W2024365188 hasAuthorship W2024365188A5028839466 @default.
- W2024365188 hasAuthorship W2024365188A5033486668 @default.
- W2024365188 hasConcept C121332964 @default.
- W2024365188 hasConcept C154945302 @default.
- W2024365188 hasConcept C19966478 @default.
- W2024365188 hasConcept C203718221 @default.
- W2024365188 hasConcept C24890656 @default.
- W2024365188 hasConcept C41008148 @default.
- W2024365188 hasConcept C50644808 @default.
- W2024365188 hasConcept C90509273 @default.
- W2024365188 hasConcept C93240960 @default.
- W2024365188 hasConceptScore W2024365188C121332964 @default.
- W2024365188 hasConceptScore W2024365188C154945302 @default.
- W2024365188 hasConceptScore W2024365188C19966478 @default.
- W2024365188 hasConceptScore W2024365188C203718221 @default.
- W2024365188 hasConceptScore W2024365188C24890656 @default.
- W2024365188 hasConceptScore W2024365188C41008148 @default.
- W2024365188 hasConceptScore W2024365188C50644808 @default.
- W2024365188 hasConceptScore W2024365188C90509273 @default.
- W2024365188 hasConceptScore W2024365188C93240960 @default.
- W2024365188 hasIssue "2" @default.
- W2024365188 hasLocation W20243651881 @default.
- W2024365188 hasLocation W20243651882 @default.
- W2024365188 hasOpenAccess W2024365188 @default.
- W2024365188 hasPrimaryLocation W20243651881 @default.
- W2024365188 hasRelatedWork W1965964592 @default.
- W2024365188 hasRelatedWork W2042495684 @default.
- W2024365188 hasRelatedWork W2122871747 @default.
- W2024365188 hasRelatedWork W2128004172 @default.
- W2024365188 hasRelatedWork W2157882971 @default.
- W2024365188 hasRelatedWork W2386387936 @default.
- W2024365188 hasRelatedWork W3114279067 @default.
- W2024365188 hasRelatedWork W3189063219 @default.
- W2024365188 hasRelatedWork W3194552545 @default.
- W2024365188 hasRelatedWork W4372183030 @default.
- W2024365188 hasVolume "22" @default.
- W2024365188 isParatext "false" @default.
- W2024365188 isRetracted "false" @default.
- W2024365188 magId "2024365188" @default.
- W2024365188 workType "article" @default.