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» Learning the Relative Importance of Features in Image Data
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164
Voted
SAC
2008
ACM
15 years 2 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
153
Voted
ECAI
2004
Springer
15 years 7 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
139
Voted
MM
2006
ACM
152views Multimedia» more  MM 2006»
15 years 9 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,...
146
Voted
BMVC
2010
15 years 1 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
126
Voted
VISUAL
1999
Springer
15 years 8 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