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» Multiple Comparisons in Induction Algorithms
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GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
15 years 5 months ago
Tracking multiple objects in non-stationary video
One of the key problems in computer vision and pattern recognition is tracking. Multiple objects, occlusion, and tracking moving objects using a moving camera are some of the chal...
Hoang Nguyen, Bir Bhanu
152
Voted
PRIS
2004
15 years 3 months ago
Comparison of Combination Methods using Spectral Clustering Ensembles
We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
André Lourenço, Ana L. N. Fred
EJWCN
2011
197views more  EJWCN 2011»
14 years 9 months ago
Comparison among Cognitive Radio Architectures for Spectrum Sensing
Recently, the growing success of new wireless applications and services has led to overcrowded licensed bands, inducing the governmental regulatory agencies to consider more flex...
Luca Bixio, Marina Ottonello, Mirco Raffetto, Carl...
TVCG
2011
126views more  TVCG 2011»
14 years 9 months ago
A Comparison of Gradient Estimation Methods for Volume Rendering on Unstructured Meshes
—This paper presents a study of gradient estimation methods for rendering unstructured-mesh volume data. Gradient estimation is necessary for rendering shaded isosurfaces and spe...
Carlos D. Correa, Robert Hero, Kwan-Liu Ma
157
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PAMI
2011
14 years 9 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang