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» Learning Mid-Level Features For Recognition
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CRV
2009
IEEE
158views Robotics» more  CRV 2009»
14 years 2 months ago
Automated Spatial-Semantic Modeling with Applications to Place Labeling and Informed Search
This paper presents a spatial-semantic modeling system featuring automated learning of object-place relations from an online annotated database, and the application of these relat...
Pooja Viswanathan, David Meger, Tristram Southey, ...
CEC
2007
IEEE
14 years 1 months ago
WAIRS: improving classification accuracy by weighting attributes in the AIRS classifier
— AIRS (Artificial Immune Recognition System) has shown itself to be a competitive classifier. It has also proved to be the most popular immune inspired classifier. However, rath...
Andrew Secker, Alex Alves Freitas
MCS
2007
Springer
14 years 1 months ago
Group-Induced Vector Spaces
The strength of classifier combination lies either in a suitable averaging over multiple experts/sources or in a beneficial integration of complementary approaches. In this paper...
Manuele Bicego, Elzbieta Pekalska, Robert P. W. Du...
CIARP
2009
Springer
13 years 11 months ago
Particle Swarm Model Selection for Authorship Verification
Authorship verification is the task of determining whether documents were or were not written by a certain author. The problem has been faced by using binary classifiers, one per a...
Hugo Jair Escalante, Manuel Montes-y-Gómez,...
ICVGIP
2004
13 years 9 months ago
Modeling Signs Using Functional Data Analysis
1 We present a functional data analysis (FDA) based method to statistically model continuous signs of the American Sign Language (ASL) for use in the recognition of signs in contin...
Sunita Nayak, Sudeep Sarkar, Kuntal Sengupta