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» Feature Level Clustering of Large Biometric Database
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SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
14 years 7 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
ACCV
2007
Springer
14 years 1 months ago
Learning Gabor Magnitude Features for Palmprint Recognition
Palmprint recognition, as a new branch of biometric technology, has attracted much attention in recent years. Various palmprint representations have been proposed for recognition. ...
Rufeng Chu, Zhen Lei, Yufei Han, Ran He, Stan Z. L...
NAACL
2004
13 years 8 months ago
Name Tagging with Word Clusters and Discriminative Training
We present a technique for augmenting annotated training data with hierarchical word clusters that are automatically derived from a large unannotated corpus. Cluster membership is...
Scott Miller, Jethran Guinness, Alex Zamanian
CVPR
2007
IEEE
14 years 9 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
ICDE
2004
IEEE
117views Database» more  ICDE 2004»
14 years 8 months ago
Probe, Cluster, and Discover: Focused Extraction of QA-Pagelets from the Deep Web
In this paper, we introduce the concept of a QA-Pagelet to refer to the content region in a dynamic page that contains query matches. We present THOR, a scalable and efficient min...
James Caverlee, Ling Liu, David Buttler