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» Learning the Relative Importance of Features in Image Data
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135
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PAMI
2006
127views more  PAMI 2006»
15 years 3 months ago
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Martin H. C. Law, Anil K. Jain
138
Voted
ICDM
2009
IEEE
156views Data Mining» more  ICDM 2009»
15 years 1 months ago
Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging
We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal ...
132
Voted
AVSS
2007
IEEE
15 years 3 months ago
People tracking across two distant self-calibrated cameras
People tracking is of fundamental importance in multicamera surveillance systems. In recent years, many approaches for multi-camera tracking have been discussed. Most methods use ...
Roman P. Pflugfelder, Horst Bischof
142
Voted
ICPR
2004
IEEE
16 years 4 months ago
Entropy-Based Measures for Clustering and SOM Topology Preservation Applied to Content-Based Image Indexing and Retrieval
Content-based image retrieval (CBIR) addresses the problem of finding images relevant to the users' information needs, based principally on low-level visual features for whic...
Markus Koskela, Jorma Laaksonen, Erkki Oja
148
Voted
CVPR
2003
IEEE
16 years 5 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman