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Analysis of Linear and Nonlinear dimensionality Reduction Methods for Gender Classification of Face Images
(2005-11)
Data in many real world applications are high dimensional and learning algorithms like neural networks may have problems in handling high dimensional data. However, the Intrinsic Dimension is often much less than the ...
Using real-valued metaclassifiers to integrate binding site predictions
(Institute of Electrical and Electronics Engineers (IEEE), 2005)
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. There is good reason to believe that predictions from these different classes of algorithms could be used in ...
Comparing computational and human measures of visual similarity
(World Scientific Publishing, 2005)
There have been many attempts to quantify visual similarity within different categories of objects, with a view to using such measures to predict impaired recognition performance. Although many studies have linked measures ...
Hierarchical topological clustering learns stock market sectors
(Institute of Electrical and Electronics Engineers (IEEE), 2005)
The breakdown of financial markets into sectors provides an intuitive classification for groups of companies. The allocation of a company to a sector is an expert task, in which the company is classified by the activity ...
Global and Feature Based Gender Classification of Faces: A Comparison of Human Performance and Computational Models
(2005)
Most computational models for gender classification use global information (the full face image) giving equal weight to the whole face area irrespective of the importance of the internal features. Here, we use a global and ...
Associative Memories with Small World Connectivity
(Springer Nature, 2005)
In this paper we report experiments designed to find the relationship between the different parameters of sparsely connected networks of perceptrons with small world connectivity patterns, acting as associative memories.