Learning and recognition of on-premise signs from weakly labeled street view images

IEEE Transactions on Image Processing

Volumn 23, Issue 3, 2014, Pages 1047-1059

  Tsai, Tsung Hung ^a   Cheng, Wen Huang ^a   You, Chuang Wen ^a   Hu, Min Chun ^b   Tsui, Arvin Wen ^c   Chi, Heng Yu ^a  

^a RESEARCH CENTER FOR INFORMATION TECHNOLOGY INNOVATION   (Taiwan)

^b NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^c INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE   (Taiwan)

Author keywords

learning and recognition; object image data set; Real world objects; street view scenes

Indexed keywords

DISTRIBUTIONAL CLUSTERING; DISTRIBUTIONAL INFORMATION; ENVIRONMENTAL CONDITIONS; IMAGE DATA; LEARNING AND RECOGNITION; PROBABILISTIC LATENT SEMANTIC ANALYSIS MODEL; REAL-WORLD OBJECTS; VISUAL OBJECT RECOGNITION;

AUGMENTED REALITY; MOBILE DEVICES; MOBILE TELECOMMUNICATION SYSTEMS; SEMANTICS;

PROBABILITY DISTRIBUTIONS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; CONSTRUCTION WORK AND ARCHITECTURAL PHENOMENA; IMAGE ENHANCEMENT; METHODOLOGY; NATURAL LANGUAGE PROCESSING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LOCATION DIRECTORIES AND SIGNS; NATURAL LANGUAGE PROCESSING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84893846216     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2014.2298982     Document Type: Article

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