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» Learning to Identify Unexpected Instances in the Test Set
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ICCV
2007
IEEE
14 years 9 months ago
An Empirical Study of Object Category Recognition: Sequential Testing with Generalized Samples
In this paper we present an empirical study of object category recognition using generalized samples and a set of sequential tests. We study 33 categories, each consisting of a sm...
Liang Lin, Shaowu Peng, Jake Porway, Song Chun Zhu...
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
13 years 5 months ago
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
ICIP
2005
IEEE
14 years 9 months ago
A complementary SVMs-based image annotation system
A novel automatic image annotation system is proposed, which integrates two sets of SVMs (Support Vector Machines), namely the MIL-based (Multiple Instance Learning) and global-fe...
Yutao Han, Xiaojun Qi
ICPR
2008
IEEE
14 years 8 months ago
Preliminary approach on synthetic data sets generation based on class separability measure
Usually, performance of classifiers is evaluated on real-world problems that mainly belong to public repositories. However, we ignore the inherent properties of these data and how...
Núria Macià, Ester Bernadó-Ma...
GLVLSI
2005
IEEE
133views VLSI» more  GLVLSI 2005»
14 years 29 days ago
Generating decision regions in analog measurement spaces
We develop a neural network that learns to separate the nominal from the faulty instances of a circuit in a measurement space. We demonstrate that the required separation boundari...
Haralampos-G. D. Stratigopoulos, Yiorgos Makris