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» Obtaining Best Parameter Values for Accurate Classification
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CVPR
2007
IEEE
14 years 9 months ago
Feasibility Boundary in Dense and Semi-Dense Stereo Matching
In stereo literature, there is no standard method for evaluating algorithms for semi-dense stereo matching. Moreover, existing evaluations for dense methods require a fixed parame...
Jan Cech, Jana Kostlivá, Radim Sára
DATE
2008
IEEE
131views Hardware» more  DATE 2008»
14 years 2 months ago
Parametric Throughput Analysis of Synchronous Data Flow Graphs
Synchronous Data Flow Graphs (SDFGs) have proved to be a very successful tool for modeling, analysis and synthesis of multimedia applications targeted at both single- and multiproc...
Amir Hossein Ghamarian, Marc Geilen, Twan Basten, ...
ICPR
2008
IEEE
14 years 9 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
MICCAI
2004
Springer
14 years 8 months ago
Shape Particle Filtering for Image Segmentation
Abstract. Deformable template models are valuable tools in medical image segmentation. Current methods elegantly incorporate global shape and appearance, but can not cope with loca...
Marleen de Bruijne, Mads Nielsen
ICDM
2010
IEEE
108views Data Mining» more  ICDM 2010»
13 years 5 months ago
Assessing Data Mining Results on Matrices with Randomization
Abstract--Randomization is a general technique for evaluating the significance of data analysis results. In randomizationbased significance testing, a result is considered to be in...
Markus Ojala