Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge

Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge

Deep neural networks (DNNs) have recently achieved remarkable performance in a myriad of applications, ranging from image recognition to language processing. Training such networks on graphics processing units (GPUs) currently offers unmatched levels of performance; however, GPUs are subject to larg...

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Bibliographic Details
Main Authors: Corey Lammie, Alex Olsen, Tony Carrick, Mostafa Rahimi Azghadi
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Machine learning (ML)
deep neural networks (DNNs)
convolutional neural networks (CNNs)
binarized neural networks (BNNs)
Internet of Things (IoT)
field programmable gate arrays (FPGAs)
Online Access:https://ieeexplore.ieee.org/document/8693488/

Internet

https://ieeexplore.ieee.org/document/8693488/

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