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» Learning the Relative Importance of Features in Image Data
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SAC
2008
ACM
15 years 5 months ago
Strangeness-based feature weighting and classification of gene expression profiles
Achieving high classification accuracy is a major challenge in the diagnosis of cancer types based on gene expression profiles. These profiles are notoriously noisy in that a larg...
Haifeng Shao, Bei Yu, Joseph H. Nadeau
ECAI
2004
Springer
15 years 11 months ago
Avoiding Data Overfitting in Scientific Discovery: Experiments in Functional Genomics
Functional genomics is a typical scientific discovery domain characterized by a very large number of attributes (genes) relative to the number of examples (observations). The dang...
Dragan Gamberger, Nada Lavrac
MM
2006
ACM
152views Multimedia» more  MM 2006»
16 years 1 months ago
Local image representations using pruned salient points with applications to CBIR
Salient points are locations in an image where there is a significant variation with respect to a chosen image feature. Since the set of salient points in an image capture import...
Hui Zhang, Rouhollah Rahmani, Sharath R. Cholleti,...
BMVC
2010
15 years 5 months ago
Iterative Hyperplane Merging: A Framework for Manifold Learning
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
Harry Strange, Reyer Zwiggelaar
VISUAL
1999
Springer
15 years 11 months ago
General Image Database Model
In this paper we propose a new General Image DataBase (GIDB) model. The model establishes taxonomy based on the systematisation of existing approaches. The GIDB model is based on t...
Peter L. Stanchev