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MIR
2006
ACM
223views Multimedia» more  MIR 2006»
14 years 3 months ago
Adaptive image retrieval using a Graph model for semantic feature integration
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...
Jana Urban, Joemon M. Jose
MM
2006
ACM
148views Multimedia» more  MM 2006»
14 years 3 months ago
Audio similarity measure by graph modeling and matching
This paper proposes a new approach for the similarity measure and ranking of audio clips by graph modeling and matching. Instead of using frame-based or salient-based features to ...
Yuxin Peng, Chong-Wah Ngo, Cuihua Fang, Xiaoou Che...
SODA
2008
ACM
127views Algorithms» more  SODA 2008»
13 years 10 months ago
Nondecreasing paths in a weighted graph or: how to optimally read a train schedule
A travel booking office has timetables giving arrival and departure times for all scheduled trains, including their origins and destinations. A customer presents a starting city a...
Virginia Vassilevska
JGT
2010
57views more  JGT 2010»
13 years 7 months ago
NZ-flows in strong products of graphs
: We prove that the strong product G1 G2 of G1 and G2 is Z3-flow contractible if and only if G1 G2 is not T K2, where T is a tree (we call T K2 a K4-tree). It follows that G1 G2 ad...
Wilfried Imrich, Iztok Peterin, Simon Spacapan, Cu...
CASES
2010
ACM
13 years 7 months ago
Instruction selection by graph transformation
Common generated instruction selections are based on tree pattern matching, but modern and custom architectures feature instructions, which cannot be covered by trees. To overcome...
Sebastian Buchwald, Andreas Zwinkau