Título:	Computer vision for larval structures identification applied to forensic science.
Autor:	OLIVEIRA, C. E. LIMA, L. R. de OLIVEIRA, G. R. A. de GONÇALVES, A. B. PISTORI, H. KOLLER, W. W.
Afiliación:	CARINA ELISEU OLIVEIRA, Universidade Católica Dom Bosco, Campo Campo Grande-MS; LUCAS RODRIGUES DE LIMA, Universidade Católica Dom Bosco, Campo Campo Grande-MS; GLAUCIA RAQUEL ASSIS DE OLIVEIRA, Universidade Católica Dom Bosco, Campo Campo Grande-MS; ARIADNE BARBOSA GONÇALVES, Universidade Católica Dom Bosco, Campo Campo Grande-MS; HEMERSON PISTORI, Universidade Católica Dom Bosco, Campo Campo Grande-MS; WILSON WERNER KOLLER, CNPGC.
Año:	2016
Referencia:	In: WORKSHOP DE VISÃO COMPUTACIONAL WVC'2016, 12., 2016. Campo Grande, MS. Proceedings... Campo Grande: UCDB/UFMS/UFGD, p. 266-270, nov. 2016.
Descripción:	The diptera maggots are used in forensic entomology to estimate the post-mortem interval (PMI). Maggots have a wide range of morphological and structural features that aid in the identification. In order to assist in the necrophagous larvae identification, this research aims to develop a software using computer vision and machine learning to automate the classification process. Diptera maggots were collected in a dead pig at the capital of Mato Grosso do Sul state, Campo Grande. The maggots were identified and photographed at a light microscope (5x objective). Next, the images were processed, the features extraction was performed using an extractor in Python language. The classification of the images were tested with AdaBoost, Random Forest, Random Tree and SMO classifiers. The SMO the best performa.
NAL Thesaurus:	Entomology Insect larvae Computer vision
Tipo de Material:	Artigo em anais e proceedings
Acceso:	openAccess
Aparece en las colecciones:	Artigo em anais de congresso (CNPGC)