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Multi-path x-D recurrent neural networks for collaborative image classification

Neurocomputing(2020)10.1016/j.neucom.2020.02.033Source: DataRank Database

Multi-path x-D recurrent neural networks for collaborative image classification is a research paper published in Neurocomputing (2020). On theSindex it has a DataRank of 0. It has been cited 12 times.

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Scored on demand from live citation data

Open Access12 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (17 grants)Impact (FWCI 1.61)OA: greenTopics (26)IDs (PubMed, PMC, OpenAlex)SDGs (3)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (11)

Yuankai Huo ORCID,Shunxing Bao ORCID,Yucheng Tang ORCID,Sanja Antic ORCID,Emily S. Epstein

Live enrichment

PubMed:32863584 PMC:PMC7454345 OpenAlex:https://openalex.org/W3006505603

National Institutes of Health

Grant: UO1 CA196405

National Institutes of Health

Grant: R01 EB017230

National Center for Research Resources

Grant: UL1 RR024975-01

Patient-Centered Outcomes Research Institute

Grant: CDRN-1306-04869

National Center for Advancing Translational Sciences

Grant: 2 UL1 TR000445-06

National Science Foundation

Grant: 1452485

CAREER: Modeling Personalized Brain Development with Big Data

NCRR NIH HHS

Grant: UL1 RR024975

NCATS NIH HHS

Grant: UL1 TR000445

NCI NIH HHS

Grant: U01 CA196405

NCI NIH HHS

Grant: P50 CA058187

National Institutes of Health

Grant: 3UL1RR024975-03S4

The Vanderbilt Institute for Clinical and Translational Research (VICTR) UL1

National Institutes of Health

Grant: 5R01EB017230-07

Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRI

National Institutes of Health

Grant: 3P50CA058187-18S1

Tissue Bank and Biomarkers Core

National Institutes of Health

Grant: 6UL1TR000445-11

The Vanderbilt Institute for Clinical and Translational Research (VICTR)

National Institutes of Health

National Science Foundation

Patient-Centered Outcomes Research Institute

FWCI

1.61

Citation Percentile

0.9%

Citation Trend

2020

2021

2022

greenLicense: Elsevier TDM

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/7454345

publisherhttps://api.elsevier.com/content/article/PII:S092523122030223X?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S092523122030223X?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.neucom.2020.02.033

Fields of Study

AI in cancer detectionDigital Imaging for Blood DiseasesAdvanced Neural Network Applications03 medical and health sciences0302 clinical medicine0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Computer scienceMNIST databaseArtificial intelligencePattern recognition (psychology)Convolutional neural networkDiscriminative modelContextual image classificationLeverage (statistics)Margin (machine learning)Recurrent neural networkStandard test imageImage (mathematics)Artificial neural networkMachine learningImage processingLongitudinalRnnCategory-irrelevant AttributesUnordered Image

Sustainable Development Goals

SDG 3: 3. Good healthSDG 7: 7. Clean energySDG 0: Reduced inequalities