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Multimodal Feature Fusion and Knowledge-Driven Learning via Experts Consult for Thyroid Nodule Classification.

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Title: Multimodal Feature Fusion and Knowledge-Driven Learning via Experts Consult for Thyroid Nodule Classification.
Authors: Avola, Danilo1, avola@di.uniroma1.it, Cinque, Luigi1, cinque@di.uniroma1.it, Fagioli, Alessio1, fagioli@di.uniroma1.it, Filetti, Sebastiano2, sebastiano.filetti@.uniroma1.it, Grani, Giorgio2, giorgio.grani@.uniroma1.it, Rodola, Emanuele2, rodola@di.uniroma1.it
Source: IEEE Transactions on Circuits & Systems for Video Technology; May2022, Vol. 32 Issue 5, p2527-2534, 8p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 156718312
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Multimodal Feature Fusion and Knowledge-Driven Learning via Experts Consult for Thyroid Nodule Classification.
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1109/TCSVT.2021.3074414
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      – Code: eng
        Text: English
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        PageCount: 8
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      – TitleFull: Multimodal Feature Fusion and Knowledge-Driven Learning via Experts Consult for Thyroid Nodule Classification.
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            NameFull: Avola, Danilo
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            – D: 01
              M: 05
              Text: May2022
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              Y: 2022
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