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Registro Completo |
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Biblioteca(s): |
Embrapa Gado de Corte. |
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Data corrente: |
25/01/2017 |
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Data da última atualização: |
10/03/2017 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
OLIVEIRA, C. E.; LIMA, L. R. de; OLIVEIRA, G. R. A. de; GONÇALVES, A. B.; PISTORI, H.; KOLLER, W. W. |
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Afiliação: |
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. |
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Título: |
Computer vision for larval structures identification applied to forensic science. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
In: WORKSHOP DE VISÃO COMPUTACIONAL WVC'2016, 12., 2016. Campo Grande, MS. Proceedings... Campo Grande: UCDB/UFMS/UFGD, p. 266-270, nov. 2016. |
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Idioma: |
Inglês |
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Conteúdo: |
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. |
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Thesaurus Nal: |
Computer vision; Entomology; Insect larvae. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/155450/1/Computer-vision-for-larval.pdf
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Marc: |
LEADER 01519nam a2200205 a 4500
001 2061783
005 2017-03-10
008 2016 bl uuuu u00u1 u #d
100 1 $aOLIVEIRA, C. E.
245 $aComputer vision for larval structures identification applied to forensic science.$h[electronic resource]
260 $aIn: WORKSHOP DE VISÃO COMPUTACIONAL WVC'2016, 12., 2016. Campo Grande, MS. Proceedings... Campo Grande: UCDB/UFMS/UFGD, p. 266-270, nov. 2016.$c2016
520 $aThe 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.
650 $aComputer vision
650 $aEntomology
650 $aInsect larvae
700 1 $aLIMA, L. R. de
700 1 $aOLIVEIRA, G. R. A. de
700 1 $aGONÇALVES, A. B.
700 1 $aPISTORI, H.
700 1 $aKOLLER, W. W.
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Registro original: |
Embrapa Gado de Corte (CNPGC) |
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| Registros recuperados : 4 | |
| 3. |  | KOTHARI, K.; BATTISTI, R.; BOOTE, K. J.; ARCHONTOULIS, S. V.; CONFALONE, A.; CONSTANTIN, J.; CUADRA, S. V.; DEBAEKE, P.; FAYE, B.; GRANT, B.; HOOGENBOOM, G.; JING, Q.; VAN DER LAAN, M.; SILVA, F. A. M. da; MARIN, F. R.; NEHBANDANI, A.; NENDEL, C.; PURCELL, L. C.; QIAN, B.; RUANE, A. C.; SCHOVING, C.; SILVA, E. H. F. M.; SMITH, W.; SOLTANI, A.; SRIVASTAVA, A.; VIEIRA JÚNIOR, N. A.; SLONE, S.; SALMERÓN, M. Are soybean models ready for climate change food impact assessments? European Journal of Agronomy, v. 135, 126482, Apr. 2022.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Cerrados. |
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| 4. | | KOTHARI, K.; BATTISTI, R.; BOOTE, K. J.; ARCHONTOULIS, S. V.; CONFALONE, A.; CONSTANTIN, J.; CUADRA, S. V.; DEBAEKE, P.; FAYE, B.; GRANT, B.; HOOGENBOOM, G.; JING, Q.; VAN DER LAAN, M.; SILVA, F. A. M. da; MARIN, F. R.; NEHBANDANI, A.; NENDEL, C.; PURCELL, L. C.; QIAN, B.; RUANE, A. C.; SCHOVING, C.; SILVA, E. H. F. M.; SMITH, W.; SOLTANI, A.; SRIVASTAVA, A.; VIEIRA JÚNIOR, N. A.; SALMERÓN, M. Evaluating differences among crop models in simulating soybean in-season growth Field Crops Research, v. 309, 109306, April 2024.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Cerrados. |
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| Registros recuperados : 4 | |
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