Matches in SemOpenAlex for { <https://semopenalex.org/work/W2964218314> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W2964218314 abstract "Recent work has shown that the end-to-end approach using convolutional neural network (CNN) is effective in various types of machine learning tasks. For audio signals, the approach takes raw waveforms as input using an 1-D convolution layer. In this paper, we improve the 1-D CNN architecture for music auto-tagging by adopting building blocks from state-of-the-art image classification models, ResNets and SENets, and adding multi-level feature aggregation to it. We compare different combinations of the modules in building CNN architectures. The results show that they achieve significant improvements over previous state-of-the-art models on the MagnaTagATune dataset and comparable results on Million Song Dataset. Furthermore, we analyze and visualize our model to show how the 1-D CNN operates." @default.
- W2964218314 created "2019-07-30" @default.
- W2964218314 creator A5049268304 @default.
- W2964218314 creator A5056437111 @default.
- W2964218314 creator A5079480701 @default.
- W2964218314 date "2018-04-01" @default.
- W2964218314 modified "2023-10-14" @default.
- W2964218314 title "Sample-Level CNN Architectures for Music Auto-Tagging Using Raw Waveforms" @default.
- W2964218314 cites W2059652044 @default.
- W2964218314 cites W2194775991 @default.
- W2964218314 cites W2526050071 @default.
- W2964218314 cites W2604509013 @default.
- W2964218314 cites W2963451564 @default.
- W2964218314 cites W3105202226 @default.
- W2964218314 doi "https://doi.org/10.1109/icassp.2018.8462046" @default.
- W2964218314 hasPublicationYear "2018" @default.
- W2964218314 type Work @default.
- W2964218314 sameAs 2964218314 @default.
- W2964218314 citedByCount "57" @default.
- W2964218314 countsByYear W29642183142012 @default.
- W2964218314 countsByYear W29642183142018 @default.
- W2964218314 countsByYear W29642183142019 @default.
- W2964218314 countsByYear W29642183142020 @default.
- W2964218314 countsByYear W29642183142021 @default.
- W2964218314 countsByYear W29642183142022 @default.
- W2964218314 countsByYear W29642183142023 @default.
- W2964218314 crossrefType "proceedings-article" @default.
- W2964218314 hasAuthorship W2964218314A5049268304 @default.
- W2964218314 hasAuthorship W2964218314A5056437111 @default.
- W2964218314 hasAuthorship W2964218314A5079480701 @default.
- W2964218314 hasBestOaLocation W29642183142 @default.
- W2964218314 hasConcept C108583219 @default.
- W2964218314 hasConcept C115961682 @default.
- W2964218314 hasConcept C123657996 @default.
- W2964218314 hasConcept C138885662 @default.
- W2964218314 hasConcept C142362112 @default.
- W2964218314 hasConcept C153180895 @default.
- W2964218314 hasConcept C153349607 @default.
- W2964218314 hasConcept C154945302 @default.
- W2964218314 hasConcept C178790620 @default.
- W2964218314 hasConcept C185592680 @default.
- W2964218314 hasConcept C197424946 @default.
- W2964218314 hasConcept C2776401178 @default.
- W2964218314 hasConcept C2779227376 @default.
- W2964218314 hasConcept C41008148 @default.
- W2964218314 hasConcept C41895202 @default.
- W2964218314 hasConcept C45347329 @default.
- W2964218314 hasConcept C50644808 @default.
- W2964218314 hasConcept C52622490 @default.
- W2964218314 hasConcept C554190296 @default.
- W2964218314 hasConcept C76155785 @default.
- W2964218314 hasConcept C81363708 @default.
- W2964218314 hasConceptScore W2964218314C108583219 @default.
- W2964218314 hasConceptScore W2964218314C115961682 @default.
- W2964218314 hasConceptScore W2964218314C123657996 @default.
- W2964218314 hasConceptScore W2964218314C138885662 @default.
- W2964218314 hasConceptScore W2964218314C142362112 @default.
- W2964218314 hasConceptScore W2964218314C153180895 @default.
- W2964218314 hasConceptScore W2964218314C153349607 @default.
- W2964218314 hasConceptScore W2964218314C154945302 @default.
- W2964218314 hasConceptScore W2964218314C178790620 @default.
- W2964218314 hasConceptScore W2964218314C185592680 @default.
- W2964218314 hasConceptScore W2964218314C197424946 @default.
- W2964218314 hasConceptScore W2964218314C2776401178 @default.
- W2964218314 hasConceptScore W2964218314C2779227376 @default.
- W2964218314 hasConceptScore W2964218314C41008148 @default.
- W2964218314 hasConceptScore W2964218314C41895202 @default.
- W2964218314 hasConceptScore W2964218314C45347329 @default.
- W2964218314 hasConceptScore W2964218314C50644808 @default.
- W2964218314 hasConceptScore W2964218314C52622490 @default.
- W2964218314 hasConceptScore W2964218314C554190296 @default.
- W2964218314 hasConceptScore W2964218314C76155785 @default.
- W2964218314 hasConceptScore W2964218314C81363708 @default.
- W2964218314 hasLocation W29642183141 @default.
- W2964218314 hasLocation W29642183142 @default.
- W2964218314 hasOpenAccess W2964218314 @default.
- W2964218314 hasPrimaryLocation W29642183141 @default.
- W2964218314 hasRelatedWork W2279398222 @default.
- W2964218314 hasRelatedWork W2295021132 @default.
- W2964218314 hasRelatedWork W2546942002 @default.
- W2964218314 hasRelatedWork W2606416966 @default.
- W2964218314 hasRelatedWork W2731899572 @default.
- W2964218314 hasRelatedWork W3156786002 @default.
- W2964218314 hasRelatedWork W4299822940 @default.
- W2964218314 hasRelatedWork W4312417841 @default.
- W2964218314 hasRelatedWork W4321369474 @default.
- W2964218314 hasRelatedWork W4366492315 @default.
- W2964218314 isParatext "false" @default.
- W2964218314 isRetracted "false" @default.
- W2964218314 magId "2964218314" @default.
- W2964218314 workType "article" @default.