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ICCV
2011
IEEE
13 years 9 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
ECCV
2006
Springer
15 years 11 months ago
Sampling Strategies for Bag-of-Features Image Classification
Abstract. Bag-of-features representations have recently become popular for content based image classification owing to their simplicity and good performance. They evolved from text...
Eric Nowak, Frédéric Jurie, Bill Tri...
BMCBI
2008
160views more  BMCBI 2008»
14 years 9 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...
IJRR
2011
159views more  IJRR 2011»
14 years 4 months ago
Visual-inertial navigation, mapping and localization: A scalable real-time causal approach
We present a model to estimate motion from monocular visual and inertial measurements. We analyze the model and characterize the conditions under which its state is observable, an...
Eagle Jones, Stefano Soatto
ICML
2004
IEEE
15 years 10 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall