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» Dimensionality Reduction with Image Data
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ACMACE
2008
ACM
15 years 5 months ago
Dimensionality reduced HRTFs: a comparative study
Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
Bill Kapralos, Nathan Mekuz, Agnieszka Kopinska, S...
128
Voted
ECCV
2006
Springer
16 years 5 months ago
Learning Nonlinear Manifolds from Time Series
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
Ruei-Sung Lin, Che-Bin Liu, Ming-Hsuan Yang, Naren...
149
Voted
ESANN
2006
15 years 4 months ago
Hierarchical markovian models for joint classification, segmentation and data reduction of hyperspectral images
Spectral classification, segmentation and data reduction are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation approach which ...
Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpou...
126
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BIOWIRE
2007
Springer
15 years 9 months ago
Beta Random Projection
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. In particular, r...
Yu-En Lu, Pietro Liò, Steven Hand
131
Voted
MM
2005
ACM
122views Multimedia» more  MM 2005»
15 years 9 months ago
Image clustering with tensor representation
We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
Xiaofei He, Deng Cai, Haifeng Liu, Jiawei Han