Title :
Identifying Pain and Hunger in Infant Cry with Classifiers Ensembles
Author :
Barajas-Montiel, Sandra E. ; Reyes-García, Carlos A.
Abstract :
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
Keywords :
biology computing; neural nets; pattern classification; support vector machines; artificial neural network; ensembles classification; infant cry classification; support vector machines; Artificial neural networks; Boosting; Feedforward neural networks; Neural networks; Pain; Pathology; Pattern classification; Pediatrics; Support vector machine classification; Support vector machines;
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2504-0
DOI :
10.1109/CIMCA.2005.1631561
