Benchmarking edge computing devices for grape bunches and trunks detection using accelerated object detection single shot multibox deep learning models-Reference-Cited by-同舟云学术

Benchmarking edge computing devices for grape bunches and trunks detection using accelerated object detection single shot multibox deep learning models

Published:2023-01 Issue: Volume:117 Page:105604
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Magalhães Sandro Costa^ORCID,dos Santos Filipe Neves^ORCID,Machado Pedro^ORCID,Moreira António Paulo^ORCID,Dias Jorge^ORCID

Funder

European Social Fund

Horizon 2020 Framework Programme

Horizon 2020

Fundação para a Ciência e a Tecnologia

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference43 articles.

1. Grape bunch and vine trunk dataset for deep learning object detection;Aguiar,2021

2. Grape bunch detection at different growth stages using deep learning quantized models;Aguiar;Agronomy,2021

3. DPU for convolutional neural network;AMD-Xilinx,2022

4. YOLACT: Real-time instance segmentation;Bolya,2019

5. T-DLA: An open-source deep learning accelerator for ternarized DNN models on embedded FPGA;Chen,2019

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