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http://www.repositorio.ufop.br/jspui/handle/123456789/12837
Título: | Combined weightless neural network FPGA architecture for deforestation surveillance and visual navigation of UAVs. |
Autor(es): | Torres, Vitor Angelo Maria Ferreira Jaimes, Brayan Rene Acevedo Ribeiro, Eduardo S. Braga, Mateus Taulois Shiguemori, Elcio Hideiti Velho, Haroldo Fraga de Campos Torres, Luiz Carlos Bambirra Braga, Antônio de Pádua |
Palavras-chave: | Classification Artificial neural networks |
Data do documento: | 2020 |
Referência: | TORRES, V. A. M. F. et al. Combined weightless neural network FPGA architecture for deforestation surveillance and visual navigation of UAVs. Engineering Applications of Artificial Intelligence, v. 87, jan. 2020. Disponível em: <https://www.sciencedirect.com/science/article/pii/S095219761930212X>. Acesso em: 10 mar. 2020. |
Resumo: | This work presents a combined weightless neural network architecture for deforestation surveillance and visual navigation of Unmanned Aerial Vehicles (UAVs). Binary images, which are required for position estimation and UAV navigation, are provided by the deforestation surveillance circuit. Learned models are evaluated in a real UAV flight over a green countryside area, while deforestation surveillance is assessed with an Amazon forest benchmarking image data. Small utilization percentage of Field Programmable Gate Arrays (FPGAs) allows for a higher degree of parallelization and block processing of larger regions of input images. |
URI: | http://www.repositorio.ufop.br/handle/123456789/12837 |
Link para o artigo: | https://www.sciencedirect.com/science/article/pii/S095219761930212X?via%3Dihub |
DOI: | https://doi.org/10.1016/j.engappai.2019.08.021 |
ISSN: | 0952-1976 |
Aparece nas coleções: | DECSI - Artigos publicados em periódicos |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
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ARTIGO_CombinedWeightlessNeural.pdf Restricted Access | 3,4 MB | Adobe PDF | Visualizar/Abrir |
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