Matches in SemOpenAlex for { <https://semopenalex.org/work/W2986579802> ?p ?o ?g. }
Showing items 1 to 58 of
58
with 100 items per page.
- W2986579802 abstract "Neuromorphic computing or neuromorphic engineering is an engineering discipline that attempts to simulate human brain function by creating circuits that mimic the shape of neurons. In the field of neuromorphic computing, neuromorphic processors are used. There are many types of neuromorphic processors, and there are neuromorphic processors implemented based on FPGAs. Neuromorphic processors use an artificial intelligence model called a spiking neural network. Each neuromorphic processor has different characteristics. For example, the spiking neural network model supported by each supported neuromorphic processor may be different. In this paper, we propose a service architecture named NAAL (Neuromorphic Architecture Abstract Layer) that enables the use of spiking neural networks by virtualizing various neuromorphic processors with different characteristics." @default.
- W2986579802 created "2019-11-22" @default.
- W2986579802 creator A5009077147 @default.
- W2986579802 creator A5015498941 @default.
- W2986579802 creator A5029905874 @default.
- W2986579802 creator A5054761941 @default.
- W2986579802 creator A5061369624 @default.
- W2986579802 creator A5085290695 @default.
- W2986579802 date "2019-09-24" @default.
- W2986579802 modified "2023-10-16" @default.
- W2986579802 title "A study on supporting spiking neural network models based on multiple neuromorphic processors" @default.
- W2986579802 cites W2024838294 @default.
- W2986579802 cites W2062258233 @default.
- W2986579802 cites W2065125569 @default.
- W2986579802 cites W2108148142 @default.
- W2986579802 cites W2783525259 @default.
- W2986579802 doi "https://doi.org/10.1145/3338840.3355692" @default.
- W2986579802 hasPublicationYear "2019" @default.
- W2986579802 type Work @default.
- W2986579802 sameAs 2986579802 @default.
- W2986579802 citedByCount "2" @default.
- W2986579802 countsByYear W29865798022020 @default.
- W2986579802 crossrefType "proceedings-article" @default.
- W2986579802 hasAuthorship W2986579802A5009077147 @default.
- W2986579802 hasAuthorship W2986579802A5015498941 @default.
- W2986579802 hasAuthorship W2986579802A5029905874 @default.
- W2986579802 hasAuthorship W2986579802A5054761941 @default.
- W2986579802 hasAuthorship W2986579802A5061369624 @default.
- W2986579802 hasAuthorship W2986579802A5085290695 @default.
- W2986579802 hasConcept C11731999 @default.
- W2986579802 hasConcept C118524514 @default.
- W2986579802 hasConcept C151927369 @default.
- W2986579802 hasConcept C154945302 @default.
- W2986579802 hasConcept C41008148 @default.
- W2986579802 hasConcept C50644808 @default.
- W2986579802 hasConceptScore W2986579802C11731999 @default.
- W2986579802 hasConceptScore W2986579802C118524514 @default.
- W2986579802 hasConceptScore W2986579802C151927369 @default.
- W2986579802 hasConceptScore W2986579802C154945302 @default.
- W2986579802 hasConceptScore W2986579802C41008148 @default.
- W2986579802 hasConceptScore W2986579802C50644808 @default.
- W2986579802 hasLocation W29865798021 @default.
- W2986579802 hasOpenAccess W2986579802 @default.
- W2986579802 hasPrimaryLocation W29865798021 @default.
- W2986579802 hasRelatedWork W2403181385 @default.
- W2986579802 hasRelatedWork W2960220682 @default.
- W2986579802 hasRelatedWork W2986579802 @default.
- W2986579802 hasRelatedWork W3031505884 @default.
- W2986579802 hasRelatedWork W3161396968 @default.
- W2986579802 hasRelatedWork W3214713078 @default.
- W2986579802 hasRelatedWork W4213353724 @default.
- W2986579802 hasRelatedWork W4306160827 @default.
- W2986579802 hasRelatedWork W4313484726 @default.
- W2986579802 hasRelatedWork W4381856503 @default.
- W2986579802 isParatext "false" @default.
- W2986579802 isRetracted "false" @default.
- W2986579802 magId "2986579802" @default.
- W2986579802 workType "article" @default.