Identifying Pain and Hunger in Infant Cry with Classifiers Ensembles

The present work presents the experiments performed with two kinds of ensembles to classify infant cry. The ones selected for testing during the presented experiments are: a boosting ensemble of artificial neural networks and a boosting ensemble of support vector machines. The design and implementat...

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Bibliographic Details
Main Authors: Barajas-Montiel, S.E., Reyes-Garcia, C.A.
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Boosting
Feedforward neural networks
Neural networks
Pain
Pathology
Pattern classification
Pediatrics
Support vector machine classification
Support vector machines
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Description
Summary:The present work presents the experiments performed with two kinds of ensembles to classify infant cry. The ones selected for testing during the presented experiments are: a boosting ensemble of artificial neural networks and a boosting ensemble of support vector machines. The design and implementation of the ensembles as well as the experiments and some of the results are shown. The experiments are aimed to classify the types of pain -no pain and hunger - no hunger cries
DOI:10.1109/CIMCA.2005.1631561