Automatic counting of Aedes Aegypti eggs deposited in ovitrap by algorithm of Digital Image Processing and Artificial Neural Network

Autor:	Lourdes Mattos Brasil, M. A. B. Rodrigues, F. G. G. Elpidio, Marcelino Monteiro de Andrade, Luan F. R. Costa, E. A. Costa
Rok vydání:	2011
Předmět:	biology Artificial neural network Computer science business.industry Pattern recognition Aedes aegypti biology.organism_classification medicine.disease Ovitrap Virology World health Dengue fever Medical services Digital image processing medicine Artificial intelligence business
Zdroj:	2011 Pan American Health Care Exchanges.
DOI:	10.1109/pahce.2011.5871865
Popis:	According to World Health Organization, Dengue is identified as one of the main pandemic viral disease in tropical and semi-tropical countries in the world. A lot of researches have divulged that the use of ovitraps has itself shown a simple and inexpensive alternative for monitoring and controlling Dengue vector, Aedes Aegypti, but generally the process of counting Dengue mosquito eggs in ovitraps is performed manually. This paper describes a proposal for automatic counting of Aedes Aegypti eggs deposited in ovitraps by Digital Image Processing techniques associated to an Artificial Neural Network.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0fb1e7fdea0f7a6676428446884277d9 https://doi.org/10.1109/pahce.2011.5871865 Zobrazit plný text záznamu