'Data annotation' diaporamas de présentation

Scientific Data Management

Scientific Data Management. CS561-Spring 2012 WPI, Mohamed eltabakh.

434 views • 39 slides

Dr. Barry Norton, Development Manager, ResearchSpace*

Book of the Dead Project: A new approach to Digital Editions of Ancient Manuscripts using CIDOC-CRM, FRBRoo and RDFa. Dr. Barry Norton, Development Manager, ResearchSpace*. * Funded by the Andrew W. Mellon Foundation * Hosted by the Collections Directorate, British Museum. Background.

303 views • 30 slides

The Infectious Disease Ontology

467 views • 25 slides

Prosody-Based Detection of Annoyance and Frustration in Communicator Dialogs

443 views • 24 slides

2014 Duke CFAR Flow Cytometry Workshop

344 views • 23 slides

2014 Duke CFAR Flow Cytometry Workshop

352 views • 23 slides

Scientific Data Annotation and Analysis

Scientific Data Annotation and Analysis. Lecture 7. Data Annotation, Processing, and Analysis. Data are expensive to gather and confounded by noise, but they are the primary means of validation in the sciences.

330 views • 18 slides

Core 2: Bioinformatics

Core 2: Bioinformatics. NCBO-Berkeley. Core 2 Specific Aims. Apply ontologies Software toolkit for describing and classifying data Capture, manage, and view data annotations Database (OBD) and interfaces to store and view annotations Investigate and compare implications

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Rubber Hits the Road: Why NEMO needs RDF

Rubber Hits the Road: Why NEMO needs RDF. Paea LePendu Stanford Center for Biomedical Informatics Research National Center for Biomedical Ontology (NCBO) Stanford University February 26, 2010. Information Processing (Where I Come In). Ontology. F ormal knowledge representation

233 views • 14 slides

Top Four Myths About Outsource Data Annotation Services

This PDF copy is describing about the top four myths about outsource data annotation services with examples to clear unambiguous stories of data annotation outsourcing and what are the exact truth about such myths. The document is shared by the experts at Cogito encourgaong the AI and ML companies, why they should outsource their data annotation needs and get the better quality data for model training at affordable cost.

114 views • 11 slides

Toward Making Online Biological Data Machine Understandable Cui Tao Data Extraction Research Group

td. Gene Model. td. Status. Gene. td. Gene Model. tr. td. Nucleotides (coding/transcript). td. Status. Source Organism. Source Organism. td. Protein. td. Nucleotides (coding/transcript). ProtoNet. td. Amino Acids. tr. Accession Number. Accession Number. td. Protein.

110 views • 1 slides