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» Training a Selection Function for Extraction
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CBMS
2009
IEEE
14 years 2 months ago
Comparative study of spine vertebra shape retrieval using learning-based feature selection
Feature extraction and selection are two important steps for shape retrieval. Given a data set, a set of features which describe the shape property from different aspects are extr...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...
ICC
2007
IEEE
141views Communications» more  ICC 2007»
14 years 2 months ago
A Hybrid Model to Detect Malicious Executables
— We present a hybrid data mining approach to detect malicious executables. In this approach we identify important features of the malicious and benign executables. These feature...
Mohammad M. Masud, Latifur Khan, Bhavani M. Thurai...
DAGM
2007
Springer
14 years 1 months ago
Learning Robust Objective Functions with Application to Face Model Fitting
Abstract. Model-based image interpretation extracts high-level information from images using a priori knowledge about the object of interest. The computational challenge is to dete...
Matthias Wimmer, Sylvia Pietzsch, Freek Stulp, Ber...
EPIA
2003
Springer
14 years 27 days ago
Evolutionary Neuroestimation of Fitness Functions
Abstract. One of the most influential factors in the quality of the solutions found by an evolutionary algorithm is the appropriateness of the fitness function. Specifically in ...
Jesús S. Aguilar-Ruiz, Daniel Mateos, Domin...
BMCBI
2008
119views more  BMCBI 2008»
13 years 7 months ago
Gene Ontology density estimation and discourse analysis for automatic GeneRiF extraction
Background: This paper describes and evaluates a sentence selection engine that extracts a GeneRiF (Gene Reference into Functions) as defined in ENTREZ-Gene based on a MEDLINE rec...
Julien Gobeill, Imad Tbahriti, Frédé...