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» A learning framework for generic sensory-motor maps
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CIVR
2006
Springer
139views Image Analysis» more  CIVR 2006»
13 years 10 months ago
NPIC: Hierarchical Synthetic Image Classification Using Image Search and Generic Features
We introduce NPIC, an image classification system that focuses on synthetic (e.g., non-photographic) images. We use class-specific keywords in an image search engine to create a no...
Fei Wang, Min-Yen Kan
WACV
2008
IEEE
14 years 22 days ago
Likelihood Map Fusion for Visual Object Tracking
Visual object tracking can be considered as a figure-ground classification task. In this paper, different features are used to generate a set of likelihood maps for each pixel i...
Zhaozheng Yin, Fatih Porikli, Robert T. Collins
MEDINFO
2007
139views Healthcare» more  MEDINFO 2007»
13 years 7 months ago
Lessons Learned from Cross-Validating Alignments between Large Anatomical Ontologies
Objectives: To compare the alignments of two large anatomical ontologies (the Foundational Model of Anatomy and GALEN) produced by three ontology alignment systems (AOAS, FALCON a...
Songmao Zhang, Olivier Bodenreider
WIDM
2004
ACM
13 years 11 months ago
A comprehensive solution to the XML-to-relational mapping problem
The use of relational database management systems (RDBMSs) to store and query XML data has attracted considerable interest with a view to leveraging their powerful and reliable da...
Sihem Amer-Yahia, Fang Du, Juliana Freire
CVPR
2010
IEEE
14 years 2 months ago
Data Fusion through Cross-modality Metric Learning using Similarity-Sensitive Hashing
Visual understanding is often based on measuring similarity between observations. Learning similarities specific to a certain perception task from a set of examples has been show...
Michael Bronstein, Alexander Bronstein, Nikos Para...