Matches in SemOpenAlex for { <https://semopenalex.org/work/W4293493864> ?p ?o ?g. }
Showing items 1 to 83 of
83
with 100 items per page.
- W4293493864 endingPage "9" @default.
- W4293493864 startingPage "1" @default.
- W4293493864 abstract "This exploration aims to study the value orientation and essence of early childhood enlightenment education based on the deep neural network (DNN). Based on the acquisition and feature learning of cross-media education big data, the DNN correlation learning of cross-media education big data, and the intelligent search of cross-media education big data based on the DNN, the intelligent search system of cross-media children's enlightenment education big data based on DNN is designed and implemented. The system includes three functional modules: the feature learning module of cross-media infant enlightenment education big data, the deep semantic correlation learning module of cross-media childhood enlightenment education big data, and the intelligent search module of cross-media childhood enlightenment education big data based on DNN. This exploration realizes the acquisition and feature learning of big data of cross-media early childhood enlightenment education, DNN learning of cross-media education big data of early childhood enlightenment, and intelligent computing of cross-media education big data based on DNN. The experimental results show that the proposed system's mean average precision (MAP) performance is improved by 15.6% on the public dataset of early childhood enlightenment education published by the Ministry of Education. Moreover, the system has also significantly improved the MAP performance of the constructed dataset in the field of early childhood enlightenment education; that is, the MAP performance has been improved by 20.6% on the dataset of Taylor's University in Malaysia (NUS-WIDE). This exploration has certain theoretical significance and empirical value for early childhood enlightenment education research." @default.
- W4293493864 created "2022-08-29" @default.
- W4293493864 creator A5010902410 @default.
- W4293493864 creator A5087096306 @default.
- W4293493864 date "2022-08-29" @default.
- W4293493864 modified "2023-10-14" @default.
- W4293493864 title "Empirical Analysis of Early Childhood Enlightenment Education Using Neural Network" @default.
- W4293493864 cites W2903857590 @default.
- W4293493864 cites W2911305823 @default.
- W4293493864 cites W2921914618 @default.
- W4293493864 cites W2935963759 @default.
- W4293493864 cites W2987545280 @default.
- W4293493864 cites W2995878487 @default.
- W4293493864 cites W3001897774 @default.
- W4293493864 cites W3006775927 @default.
- W4293493864 cites W3032508718 @default.
- W4293493864 cites W3080932060 @default.
- W4293493864 cites W3083985280 @default.
- W4293493864 cites W3092008332 @default.
- W4293493864 cites W3101352428 @default.
- W4293493864 cites W3164124334 @default.
- W4293493864 cites W3211299674 @default.
- W4293493864 cites W4200045448 @default.
- W4293493864 cites W4205950066 @default.
- W4293493864 cites W4223917550 @default.
- W4293493864 cites W4250544101 @default.
- W4293493864 doi "https://doi.org/10.1155/2022/3601941" @default.
- W4293493864 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36072750" @default.
- W4293493864 hasPublicationYear "2022" @default.
- W4293493864 type Work @default.
- W4293493864 citedByCount "0" @default.
- W4293493864 crossrefType "journal-article" @default.
- W4293493864 hasAuthorship W4293493864A5010902410 @default.
- W4293493864 hasAuthorship W4293493864A5087096306 @default.
- W4293493864 hasBestOaLocation W42934938641 @default.
- W4293493864 hasConcept C108583219 @default.
- W4293493864 hasConcept C111472728 @default.
- W4293493864 hasConcept C124101348 @default.
- W4293493864 hasConcept C138885662 @default.
- W4293493864 hasConcept C154945302 @default.
- W4293493864 hasConcept C2522767166 @default.
- W4293493864 hasConcept C2776401178 @default.
- W4293493864 hasConcept C2780326160 @default.
- W4293493864 hasConcept C41008148 @default.
- W4293493864 hasConcept C41895202 @default.
- W4293493864 hasConcept C49774154 @default.
- W4293493864 hasConcept C50644808 @default.
- W4293493864 hasConcept C75684735 @default.
- W4293493864 hasConceptScore W4293493864C108583219 @default.
- W4293493864 hasConceptScore W4293493864C111472728 @default.
- W4293493864 hasConceptScore W4293493864C124101348 @default.
- W4293493864 hasConceptScore W4293493864C138885662 @default.
- W4293493864 hasConceptScore W4293493864C154945302 @default.
- W4293493864 hasConceptScore W4293493864C2522767166 @default.
- W4293493864 hasConceptScore W4293493864C2776401178 @default.
- W4293493864 hasConceptScore W4293493864C2780326160 @default.
- W4293493864 hasConceptScore W4293493864C41008148 @default.
- W4293493864 hasConceptScore W4293493864C41895202 @default.
- W4293493864 hasConceptScore W4293493864C49774154 @default.
- W4293493864 hasConceptScore W4293493864C50644808 @default.
- W4293493864 hasConceptScore W4293493864C75684735 @default.
- W4293493864 hasLocation W42934938641 @default.
- W4293493864 hasLocation W42934938642 @default.
- W4293493864 hasLocation W42934938643 @default.
- W4293493864 hasLocation W42934938644 @default.
- W4293493864 hasOpenAccess W4293493864 @default.
- W4293493864 hasPrimaryLocation W42934938641 @default.
- W4293493864 hasRelatedWork W1984020445 @default.
- W4293493864 hasRelatedWork W2520046485 @default.
- W4293493864 hasRelatedWork W3003223715 @default.
- W4293493864 hasRelatedWork W3013509985 @default.
- W4293493864 hasRelatedWork W3014300295 @default.
- W4293493864 hasRelatedWork W3119203814 @default.
- W4293493864 hasRelatedWork W3198084416 @default.
- W4293493864 hasRelatedWork W3209328123 @default.
- W4293493864 hasRelatedWork W4213286019 @default.
- W4293493864 hasRelatedWork W4320068940 @default.
- W4293493864 hasVolume "2022" @default.
- W4293493864 isParatext "false" @default.
- W4293493864 isRetracted "false" @default.
- W4293493864 workType "article" @default.