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PAMI
2010
190views more  PAMI 2010»
13 years 5 months ago
OBJCUT: Efficient Segmentation Using Top-Down and Bottom-Up Cues
—We present a probabilistic method for segmenting instances of a particular object category within an image. Our approach overcomes the deficiencies of previous segmentation tech...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
CORR
2006
Springer
153views Education» more  CORR 2006»
13 years 7 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
SIGMOD
2009
ACM
180views Database» more  SIGMOD 2009»
14 years 7 months ago
Indexing correlated probabilistic databases
With large amounts of correlated probabilistic data being generated in a wide range of application domains including sensor networks, information extraction, event detection etc.,...
Bhargav Kanagal, Amol Deshpande
RTCSA
1999
IEEE
13 years 11 months ago
A Symbolic Model Checker for Testing ASTRAL Real-Time Specifications
ASTRAL is a high-level formal specification language for real-time (infinite state) systems. It is provided with structuring mechanisms that allow one to build modularized specifi...
Zhe Dang, Richard A. Kemmerer
CEC
2007
IEEE
13 years 11 months ago
Mining association rules from databases with continuous attributes using genetic network programming
Most association rule mining algorithms make use of discretization algorithms for handling continuous attributes. Discretization is a process of transforming a continuous attribute...
Karla Taboada, Eloy Gonzales, Kaoru Shimada, Shing...