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dc.contributor.authorSong, Yale
dc.contributor.authorDavis, Randall
dc.contributor.authorMa, Kaichen
dc.contributor.authorPenney, Dana L.
dc.date.accessioned2017-07-25T17:48:51Z
dc.date.available2017-07-25T17:48:51Z
dc.date.issued2016-07
dc.identifier.urihttp://hdl.handle.net/1721.1/110839
dc.description.abstractWe describe a sketch interpretation system that detects and classifies clock numerals created by subjects taking the Clock Drawing Test, a clinical tool widely used to screen for cognitive impairments (e.g., dementia). We describe how it balances appearance and context, and document its performance on some 2,000 drawings (about 24K clock numerals) produced by a wide spectrum of patients. We calibrate the utility of different forms of context, describing experiments with Conditional Random Fields trained and tested using a variety of features. We identify context that contributes to interpreting otherwise ambiguous or incomprehensible strokes. We describe ST-slices, a novel representation that enables “unpeeling” the layers of ink that result when people overwrite, which often produces ink impossible to analyze if only the final drawing is examined. We characterize when ST-slices work, calibrate their impact on performance, and consider their breadth of applicabilityen_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant IIS-1404494)en_US
dc.description.sponsorshipREW Research and Education Institutionen_US
dc.language.isoen_US
dc.publisherAssociation for the Advancement of Artificial Intelligenceen_US
dc.relation.isversionofhttps://www.ijcai.org/proceedings/2016en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT Web Domainen_US
dc.titleBalancing appearance and context in sketch interpretationen_US
dc.typeArticleen_US
dc.identifier.citationSong, Yale, Randall Davis, Kaichen Ma and Dana L. Penney. "Balancing Appearance and Context in Sketch Interpretation." Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, New York, New York, USA 9–15 July 2016.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorSong, Yale
dc.contributor.mitauthorDavis, Randall
dc.contributor.mitauthorMa, Kaichen
dc.relation.journalProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligenceen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsSong, Yale ; Davis, Randall ; Ma, Kaichen ; Penney, Dana L.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-5232-7281
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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