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ICCV
2009
IEEE
15 years 2 months ago
Multi-Scale Object Detection by Clustering Lines
Object detection in cluttered, natural scenes has a high complexity since many local observations compete for object hypotheses. Voting methods provide an efficient solution to ...
Bjorn Ommer, Jitendra Malik
SDM
2007
SIAM
176views Data Mining» more  SDM 2007»
13 years 10 months ago
Adaptive Concept Learning through Clustering and Aggregation of Relational Data
We introduce a new approach for Clustering and Aggregating Relational Data (CARD). We assume that data is available in a relational form, where we only have information about the ...
Hichem Frigui, Cheul Hwang
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 9 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
FSKD
2005
Springer
162views Fuzzy Logic» more  FSKD 2005»
14 years 2 months ago
Fuzzy-C-Mean Determines the Principle Component Pairs to Estimate the Degree of Emotion from Facial Expressions
Although many systems exist for automatic classification of faces according to their emotional expression, these systems do not explicitly estimate the strength of given expression...
M. Ashraful Amin, Nitin V. Afzulpurkar, Matthew N....
CINQ
2004
Springer
131views Database» more  CINQ 2004»
14 years 2 months ago
Model-Independent Bounding of the Supports of Boolean Formulae in Binary Data
Abstract. Data mining algorithms such as the Apriori method for finding frequent sets in sparse binary data can be used for efficient computation of a large number of summaries fr...
Artur Bykowski, Jouni K. Seppänen, Jaakko Hol...