Identifying Pain and Hunger in Infant Cry with Classifiers Ensembles

Autor:	C.A. Reyes-Garcia, S.E. Barajas-Montiel
Rok vydání:	2006
Předmět:	Support vector machine Boosting (machine learning) Artificial neural network Computer science business.industry Artificial intelligence Machine learning computer.software_genre business Infant crying computer
Zdroj:	CIMCA/IAWTIC
DOI:	10.1109/cimca.2005.1631561
Popis:	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
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1f8c4ca91976d11eb578487432f030d5 https://doi.org/10.1109/cimca.2005.1631561 Zobrazit plný text záznamu