Perceptual annotation: Measuring human vision to improve computer vision

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 36, Issue 8, 2014, Pages 1679-1686

  Scheirer, Walter J ^a   Anthony, Samuel E ^b   Nakayama, Ken ^b   Cox, David D ^a  

^a HARVARD UNIVERSITY   (United States)

^b HARVARD UNIVERSITY   (United States)

Author keywords

citizen science; face detection; Machine learning; psychology; psychometrics; psychophysics; regularization; support vector machines; visual recognition

Indexed keywords

FACE RECOGNITION; LEARNING SYSTEMS; PHYSICS; PSYCHOPHYSIOLOGY; SUPPORT VECTOR MACHINES;

CITIZEN SCIENCE; PSYCHOLOGY; PSYCHOMETRICS; PSYCHOPHYSICS; REGULARIZATION; VISUAL RECOGNITION;

ARTIFICIAL INTELLIGENCE;

ANATOMY AND HISTOLOGY; AUTOMATED PATTERN RECOGNITION; FACE; FACTUAL DATABASE; FEMALE; HUMAN; INFORMATION PROCESSING; MACHINE LEARNING; MALE; PATTERN RECOGNITION; PHYSIOLOGY; PROCEDURES; PSYCHOPHYSICS; SUPPORT VECTOR MACHINE;

DATA CURATION; DATABASES, FACTUAL; FACE; FEMALE; HUMANS; MACHINE LEARNING; MALE; PATTERN RECOGNITION, AUTOMATED; PATTERN RECOGNITION, VISUAL; PSYCHOPHYSICS; SUPPORT VECTOR MACHINE;

EID: 84904206230     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2013.2297711     Document Type: Article

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