Hybrid Human-Machine Vision Systems: Image Annotation using Crowds, Experts and Machines

Hybrid Human-Machine Vision Systems: Image Annotation using Crowds, Experts and Machines

The amount of digital image and video data keeps increasing at an ever-faster rate. While "big data" holds the promise of leading science to new discoveries, raw image data in itself is not of much use. In order to statistically analyze the data, it must be quantified and annotated. We arg...

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Bibliographic Details
Main Author: Welinder, Nils Peter Egon
Format: Others
Published: 2012
Online Access:https://thesis.library.caltech.edu/7095/1/thesis-submitted.pdf
Welinder, Nils Peter Egon (2012) Hybrid Human-Machine Vision Systems: Image Annotation using Crowds, Experts and Machines. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/N6A2-F347. https://resolver.caltech.edu/CaltechTHESIS:05302012-110814322 <https://resolver.caltech.edu/CaltechTHESIS:05302012-110814322>

Internet

https://thesis.library.caltech.edu/7095/1/thesis-submitted.pdf
Welinder, Nils Peter Egon (2012) Hybrid Human-Machine Vision Systems: Image Annotation using Crowds, Experts and Machines. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/N6A2-F347. https://resolver.caltech.edu/CaltechTHESIS:05302012-110814322 <https://resolver.caltech.edu/CaltechTHESIS:05302012-110814322>

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