Por favor, use este identificador para citar o enlazar este ítem:
http://www.repositorio.ufop.br/jspui/handle/123456789/15311
Título : | Combined weightless neural network FPGA architecture for deforestation surveillance and visual navigation of UAVs. |
Autor : | Torres, Vitor Angelo Maria Ferreira Jaimes, Brayan Rene Acevedo Ribeiro, Eduardo da Silva Braga, Mateus Taulois Shiguemori, Elcio Hideit Velho, Haroldo Fraga de Campos Torres, Luiz Carlos Bambirra Braga, Antônio de Pádua |
Palabras clave : | Classification Artificial neural networks |
Fecha de publicación : | 2020 |
Citación : | 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, artigo 103227, 2020. Disponível em: <https://www.sciencedirect.com/science/article/pii/S095219761930212X>. Acesso em: 29 abr. 2022. |
Resumen : | 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/jspui/handle/123456789/15311 |
metadata.dc.identifier.uri2: | https://www.sciencedirect.com/science/article/pii/S095219761930212X |
metadata.dc.identifier.doi: | https://doi.org/10.1016/j.engappai.2019.08.021 |
ISSN : | 0952-1976 |
Aparece en las colecciones: | DECSI - Artigos publicados em periódicos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
ARTIGO_CombinedWeightlessNeural.pdf Restricted Access | 3,4 MB | Adobe PDF | Visualizar/Abrir |
Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.