Customizable FPGA-based hardware accelerator for standard convolution processes empowered with quantization applied to LiDAR data

In recent years there has been an increase in the number of research and developments in deep learning solutions for object detection applied to driverless vehicles. This application benefited from the growing trend felt in innovative perception solutions, such as LiDAR sensors. Currently, this is t...

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Detalhes bibliográficos
Autor principal: Silva, João Pedro Duarte (author)
Outros Autores: Pereira, Pedro Miguel Coelho (author), Machado, Rui (author), Névoa, Rafael (author), Melo-Pinto, Pedro (author), Fernandes, Duarte (author)
Formato: article
Idioma:eng
Publicado em: 2022
Assuntos:
convolutional neural network (CNN)
hardware accelerator
field-programmable gate array (FPGA)
light detection and ranging (LiDAR)
quantization
object detection
Ciências Naturais::Ciências da Computação e da Informação
Science & Technology
Texto completo:https://hdl.handle.net/1822/79802
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/79802

Texto Completo

https://hdl.handle.net/1822/79802

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