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CVPR
2006
IEEE
16 years 9 months ago
Unsupervised Learning of Categories from Sets of Partially Matching Image Features
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Kristen Grauman, Trevor Darrell
ICIP
2001
IEEE
16 years 8 months ago
Feature coincidence trees for registration of ultrasound breast images
Registration of an image, the query or reference, to a database of rotated and translated exemplars constitutes an important image retrieval and indexing application which arises i...
Huzefa Neemuchwala, Alfred O. Hero, Paul L. Carson
ICML
2007
IEEE
16 years 7 months ago
Spectral feature selection for supervised and unsupervised learning
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
Zheng Zhao, Huan Liu
KDD
2002
ACM
126views Data Mining» more  KDD 2002»
16 years 7 months ago
Integrating feature and instance selection for text classification
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
Dimitris Fragoudis, Dimitris Meretakis, Spiros Lik...
SMI
2008
IEEE
146views Image Analysis» more  SMI 2008»
16 years 1 months ago
SHREC'08 entry: Local volumetric features for 3D model retrieval
In this paper, we describe a method of shape-based 3D model retrieval that employs a set of 3D, local, multi-scale features extracted from a voxel representation of a 3D model to ...
Kunio Osada, Takahiko Furuya, Ryutarou Ohbuchi