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» Learning Models for Object Recognition
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ML
2007
ACM
106views Machine Learning» more  ML 2007»
14 years 9 months ago
Surrogate maximization/minimization algorithms and extensions
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
DSP
2008
14 years 8 months ago
On statistical approaches to target silhouette classification in difficult conditions
In this paper we present a methodical evaluation of the performance of a new and two traditional approaches to automatic target recognition (ATR) based on silhouette representatio...
Conrad Sanderson, Danny Gibbins, Stephen Searle
CVPR
2003
IEEE
15 years 12 months ago
Multi-scale Phase-based Local Features
Local feature methods suitable for image feature based object recognition and for the estimation of motion and structure are composed of two steps, namely the `where' and `wh...
Gustavo Carneiro, Allan D. Jepson
ICALT
2008
IEEE
15 years 4 months ago
LEMAT: A Project for Innovation in Teaching Mathematics
“Lemat” is an acronym for Libro Electrónico de Matemáticas, which means Electronic Book of Mathematics. It is a project developed by a group of teachers at secondary school ...
Beatriz Porras, Jose A. Cordon, Juan Manuel Olazab...
ICMCS
2006
IEEE
192views Multimedia» more  ICMCS 2006»
15 years 3 months ago
Classifier Optimization for Multimedia Semantic Concept Detection
In this paper, we present an AUC (i.e., the Area Under the Curve of Receiver Operating Characteristics (ROC)) maximization based learning algorithm to design the classifier for ma...
Sheng Gao, Qibin Sun