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» Learning the Relative Importance of Features in Image Data
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ICCV
2001
IEEE
14 years 10 months ago
Feature Selection from Huge Feature Sets
The number of features that can be computed over an image is, for practical purposes, limitless. Unfortunately, the number of features that can be computed and exploited by most c...
José Bins, Bruce A. Draper
CVPR
2010
IEEE
13 years 8 months ago
Learning kernels for variants of normalized cuts: Convex relaxations and applications
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
Lopamudra Mukherjee, Vikas Singh, Jiming Peng, Chr...
ICIP
2007
IEEE
14 years 2 months ago
Learning Appearance Primitives of Iris Images for Ethnic Classification
Iris pattern is commonly regarded as a kind of phenotypic feature without relation to genes. In our previous work, we argued that iris texture is race related, and its genetic inf...
Xianchao Qiu, Zhenan Sun, Tieniu Tan
ICDM
2006
IEEE
152views Data Mining» more  ICDM 2006»
14 years 2 months ago
Application of Graph-based Data Mining to Metabolic Pathways
We present a method for finding biologically meaningful patterns on metabolic pathways using the SUBDUE graph-based relational learning system. A huge amount of biological data t...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
CVPR
2011
IEEE
13 years 10 days ago
Effective 3D Object Detection and Regression Using Probabilistic Segmentation Features in CT Images
3D object detection and importance regression/ranking are at the core for semantically interpreting 3D medical images of computer aided diagnosis (CAD). In this paper, we propose ...
Le Lu, Jinbo Bi, Matthias Wolf, Marcos Salganicoff