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Complex visual question answering based on uniform form and content
Complex visual question answering based on uniform form and content
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Complex visual question answering based on uniform form and content

Applied intelligence (Dordrecht, Netherlands), 2024-03, Vol.54 (6), p.4602-4620 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;ISSN: 0924-669X ;EISSN: 1573-7497 ;DOI: 10.1007/s10489-024-05383-4

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CLSTM-SNP: Convolutional Neural Network to Enhance Spiking Neural P Systems for Named Entity Recognition Based on Long Short-Term Memory Network
CLSTM-SNP: Convolutional Neural Network to Enhance Spiking Neural P Systems for Named Entity Recognition Based on Long Short-Term Memory Network
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Article 		Add to My Research

CLSTM-SNP: Convolutional Neural Network to Enhance Spiking Neural P Systems for Named Entity Recognition Based on Long Short-Term Memory Network

Neural processing letters, 2024-04, Vol.56 (2), p.109 [Peer Reviewed Journal]

The Author(s) 2024 ;The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1370-4621 ;EISSN: 1573-773X ;DOI: 10.1007/s11063-024-11576-2

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