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» Algorithms for Large, Sparse Network Alignment Problems
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ICCV
1999
IEEE
16 years 4 months ago
Finding People by Sampling
We show how to use a sampling method to find sparsely clad people in static images. People are modeled as an assembly of nine cylindrical segments. Segments are found using an EM ...
Sergey Ioffe, David A. Forsyth
129
Voted
WWW
2008
ACM
16 years 3 months ago
Application of bitmap index to information retrieval
To solve this problem, we devised the HS-bitmap index, which is hierarchically comprised of compressed data of summary bits. A summary bit in an upper matrix is obtained by logical...
Kengo Fujioka, Yukio Uematsu, Makoto Onizuka
106
Voted
SIGIR
2005
ACM
15 years 8 months ago
Optimization strategies for complex queries
Previous research into the efficiency of text retrieval systems has dealt primarily with methods that consider inverted lists in sequence; these methods are known as term-at-a-tim...
Trevor Strohman, Howard R. Turtle, W. Bruce Croft
95
Voted
ICAISC
2004
Springer
15 years 8 months ago
Relevance LVQ versus SVM
Abstract. The support vector machine (SVM) constitutes one of the most successful current learning algorithms with excellent classification accuracy in large real-life problems an...
Barbara Hammer, Marc Strickert, Thomas Villmann
CIMAGING
2009
184views Hardware» more  CIMAGING 2009»
15 years 3 months ago
Fast space-varying convolution and its application in stray light reduction
Space-varying convolution often arises in the modeling or restoration of images captured by optical imaging systems. For example, in applications such as microscopy or photography...
Jianing Wei, Guangzhi Cao, Charles A. Bouman, Jan ...