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» Learning the parts of objects by auto-association
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ICML
2008
IEEE
14 years 8 months ago
Boosting with incomplete information
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
Feng Jiao, Gholamreza Haffari, Greg Mori, Shaojun ...
ML
2002
ACM
123views Machine Learning» more  ML 2002»
13 years 7 months ago
Feature Generation Using General Constructor Functions
Most classification algorithms receive as input a set of attributes of the classified objects. In many cases, however, the supplied set of attributes is not sufficient for creatin...
Shaul Markovitch, Dan Rosenstein
IROS
2009
IEEE
201views Robotics» more  IROS 2009»
14 years 2 months ago
Modeling tool-body assimilation using second-order Recurrent Neural Network
— Tool-body assimilation is one of the intelligent human abilities. Through trial and experience, humans are capable of using tools as if they are part of their own bodies. This ...
Shun Nishide, Tatsuhiro Nakagawa, Tetsuya Ogata, J...
MIR
2004
ACM
236views Multimedia» more  MIR 2004»
14 years 1 months ago
Boosting contextual information in content-based image retrieval
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
ISBI
2009
IEEE
14 years 2 months ago
Lesion Detection and Segmentation in Uterine Cervix Images Using an Arc-Level MRF
This study develops a procedure for automatic extraction and segmentation of a class-specific object (or region) by learning class-specific boundaries. We present and evaluate t...
Amir Alush, Hayit Greenspan, Jacob Goldberger