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| BARBEDO, J. G. A.; KOENIGKAN, L. V.; SANTOS, P. M.; RIBEIRO, A. R. B.. |
| Abstract: The management of livestock in extensive production systems may be challenging, especially in large areas. Using Unmanned Aerial Vehicles (UAVs) to collect images from the area of interest is quickly becoming a viable alternative, but suitable algorithms for extraction of relevant information from the images are still rare. This article proposes a method for counting cattle which combines a deep learning model for rough animal location, color space manipulation to increase contrast between animals and background, mathematical morphology to isolate the animals and infer the number of individuals in clustered groups, and image matching to take into account image overlap. Using Nelore and Canchim breeds as a case study, the proposed approach yields... |
| Tipo: Artigo de periódico |
Palavras-chave: Redes neurais; Rede neural convolucional; Veículo aéreo não tripulado; Canchim breed; Nelore breed; Convolutional neural networks; Mathematical morphology; Deep learning mode; Gado de Corte; Gado Nelore; Gado Canchim; Unmanned aerial vehicles; Neural networks. |
| Ano: 2020 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1121664 |
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| BARBEDO, J. G. A.; KOENIGKAN, L. V.; SANTOS, T. T.; SANTOS, P. M.. |
| Abstract: Unmanned aerial vehicles (UAVs) are being increasingly viewed as valuable tools to aid the management of farms. This kind of technology can be particularly useful in the context of extensive cattle farming, as production areas tend to be expansive and animals tend to be more loosely monitored. With the advent of deep learning, and convolutional neural networks (CNNs) in particular, extracting relevant information from aerial images has become more effective. Despite the technological advancements in drone, imaging and machine learning technologies, the application of UAVs for cattle monitoring is far from being thoroughly studied, with many research gaps still remaining. In this context, the objectives of this study were threefold: (1) to... |
| Tipo: Artigo de periódico |
Palavras-chave: Veículo aéreo não tripulado; Redes neurais; Drone; Aprendizado profundo; Convolutional neural networks; Deep learning; Canchim breed; Nelore breed; Gado de Corte; Gado Canchim; Gado Nelore; Cattle; Unmanned aerial vehicles. |
| Ano: 2019 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1116449 |
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| Veneroni,Gisele Batista; Meirelles,Sarah Laguna; Oliveira,Henrique Nunes de; Alencar,Maurício Mello de; Gasparin,Gustavo; Gouveia,João José de Simoni; Cervini,Marcelo; Regitano,Luciana Correia de Almeida. |
| Canchim, a synthetic breed of cattle derived from the Charolais and Zebu group has been used in the beef-cattle industry in Brazil as an alternative for intensifying production. One of the main concerns with this breed is its poor fat deposition and consequently, there is an effort to increase the performance for this trait. The thyroglobulin gene is located in a QTL region for fat deposition, and reports describe the influence of a polymorphism in the 5´ leader sequence of that gene on marbling and subcutaneous fat thickness. This study analyzed the association of this polymorphism in the thyroglobulin gene, as well as of two flanking microsatellite markers, CSSM066 and ILSTS011, with backfat thickness in 987 Canchim beef cattle. The CSSM066 and ILSTS011... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Canchim breed; Fat deposition; Molecular markers; Candidate gene. |
| Ano: 2012 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162012000100001 |
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