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» Learning SVMs from Sloppily Labeled Data
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ECCV
2008
Springer
14 years 11 months ago
Beyond Nouns: Exploiting Prepositions and Comparative Adjectives for Learning Visual Classifiers
Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
Abhinav Gupta, Larry S. Davis
TFS
2011
194views Education» more  TFS 2011»
13 years 4 months ago
Top-Down Induction of Fuzzy Pattern Trees
Fuzzy pattern tree induction was recently introduced as a novel machine learning method for classification. Roughly speaking, a pattern tree is a hierarchical, tree-like structur...
R. Senge, Eyke Hüllermeier
LREC
2010
131views Education» more  LREC 2010»
13 years 10 months ago
A Semi-supervised Type-based Classification of Adjectives: Distinguishing Properties and Relations
We present a semi-supervised machine-learning approach for the classification of adjectives into property- vs. relationdenoting adjectives, a distinction that is highly relevant f...
Matthias Hartung, Anette Frank
VLSISP
2010
254views more  VLSISP 2010»
13 years 7 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
SMC
2010
IEEE
139views Control Systems» more  SMC 2010»
13 years 7 months ago
Pin-pointing concept descriptions
In this study, the task of obtaining accurate and comprehensible concept descriptions of a specific set of production instances has been investigated. The suggested method, inspire...
Cecilia Sönströd, Ulf Johansson, Henrik ...