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Learning to Segment from Noisy Annotations: A Spatial Correction Approach

arXiv (Cornell University)(2023)10.48550/arxiv.2308.02498Source: DataRank Database

Learning to Segment from Noisy Annotations: A Spatial Correction Approach is a research paper published in arXiv (Cornell University) (2023). On theSindex it has a DataRank of 0. It has been cited 3 times.

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Open Access3 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)OA: greenTopics (31)IDs (PubMed, OpenAlex)

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 (6)

Yikai Zhang ORCID,Songzhu Zheng,Mayank Goswami ORCID,Prateek Prasanna ORCID,Chao Chen ORCID

Live enrichment

PubMed:19022398 OpenAlex:https://openalex.org/W4385680560

National Institutes of Health

Grant: 1R21CA258493-01A1

Computerized platform for interactive annotation and topological characterization of tumor associated vasculature for predicting response to immunotherapy in lung cancer

National Science Foundation

Grant: 2144901

CAREER: Topology-Driven Learning for Biomedical Imaging Informatics

National Science Foundation

Grant: 1910873

AF: Small: RUI: Towards Resolving the Dynamic Optimality Conjecture.

greenLicense: arXiv Non-Exclusive Distribution

repositoryhttps://arxiv.org/pdf/2308.02498

repositoryhttp://arxiv.org/abs/2308.02498

repositoryhttps://doi.org/10.48550/arxiv.2308.02498

https://dx.doi.org/10.48550/arxiv.2308.02498

https://openreview.net/forum?id=Qc_OopMEBnC

Fields of Study

Machine Learning and Data ClassificationAdvanced Neural Network ApplicationsImage and Object Detection TechniquesImage and Video Processing (eess.IV)Computer Vision and Pattern Recognition (cs.CV)Machine Learning (cs.LG)FOS: Electrical engineering, electronic engineering, information engineeringFOS: Computer and information sciences0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Computer scienceCorrectnessSegmentationArtificial intelligenceNoise (video)AnnotationPattern recognition (psychology)PixelImage segmentationDeep neural networksImage (mathematics)Artificial neural networkAlgorithmFOS: Computer and information sciencesComputer Science - Machine LearningComputer Vision and Pattern Recognition (cs.CV)Image and Video Processing (eess.IV)Computer Science - Computer Vision and Pattern RecognitionFOS: Electrical engineering, electronic engineering, information engineeringElectrical Engineering and Systems Science - Image and Video ProcessingMachine Learning (cs.LG)