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Design of Citrus Fruit Detection System Based on Mobile Platform and Edge Computer Device

Citrus fruit detection can provide technical support for fine management and yield determination of citrus orchards. Accurate detection of citrus fruits in mountain orchards is challenging because of leaf occlusion and citrus fruit mutual occlusion of different fruits. This paper presents a citrus d...

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Autores principales: Huang, Heqing, Huang, Tongbin, Li, Zhen, Lyu, Shilei, Hong, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747137/
https://www.ncbi.nlm.nih.gov/pubmed/35009602
http://dx.doi.org/10.3390/s22010059
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author Huang, Heqing
Huang, Tongbin
Li, Zhen
Lyu, Shilei
Hong, Tao
author_facet Huang, Heqing
Huang, Tongbin
Li, Zhen
Lyu, Shilei
Hong, Tao
author_sort Huang, Heqing
collection PubMed
description Citrus fruit detection can provide technical support for fine management and yield determination of citrus orchards. Accurate detection of citrus fruits in mountain orchards is challenging because of leaf occlusion and citrus fruit mutual occlusion of different fruits. This paper presents a citrus detection task that combines UAV data collection, AI embedded device, and target detection algorithm. The system used a small unmanned aerial vehicle equipped with a camera to take full-scale pictures of citrus trees; at the same time, we extended the state-of-the-art model target detection algorithm, added the attention mechanism and adaptive fusion feature method, improved the model’s performance; to facilitate the deployment of the model, we used the pruning method to reduce the amount of model calculation and parameters. The improved target detection algorithm is ported to the edge computing end to detect the data collected by the unmanned aerial vehicle. The experiment was performed on the self-made citrus dataset, the detection accuracy was 93.32%, and the processing speed at the edge computing device was 180 ms/frame. This method is suitable for citrus detection tasks in the mountainous orchard environment, and it can help fruit growers to estimate their yield.
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spelling pubmed-87471372022-01-11 Design of Citrus Fruit Detection System Based on Mobile Platform and Edge Computer Device Huang, Heqing Huang, Tongbin Li, Zhen Lyu, Shilei Hong, Tao Sensors (Basel) Article Citrus fruit detection can provide technical support for fine management and yield determination of citrus orchards. Accurate detection of citrus fruits in mountain orchards is challenging because of leaf occlusion and citrus fruit mutual occlusion of different fruits. This paper presents a citrus detection task that combines UAV data collection, AI embedded device, and target detection algorithm. The system used a small unmanned aerial vehicle equipped with a camera to take full-scale pictures of citrus trees; at the same time, we extended the state-of-the-art model target detection algorithm, added the attention mechanism and adaptive fusion feature method, improved the model’s performance; to facilitate the deployment of the model, we used the pruning method to reduce the amount of model calculation and parameters. The improved target detection algorithm is ported to the edge computing end to detect the data collected by the unmanned aerial vehicle. The experiment was performed on the self-made citrus dataset, the detection accuracy was 93.32%, and the processing speed at the edge computing device was 180 ms/frame. This method is suitable for citrus detection tasks in the mountainous orchard environment, and it can help fruit growers to estimate their yield. MDPI 2021-12-23 /pmc/articles/PMC8747137/ /pubmed/35009602 http://dx.doi.org/10.3390/s22010059 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Huang, Heqing
Huang, Tongbin
Li, Zhen
Lyu, Shilei
Hong, Tao
Design of Citrus Fruit Detection System Based on Mobile Platform and Edge Computer Device
title Design of Citrus Fruit Detection System Based on Mobile Platform and Edge Computer Device
title_full Design of Citrus Fruit Detection System Based on Mobile Platform and Edge Computer Device
title_fullStr Design of Citrus Fruit Detection System Based on Mobile Platform and Edge Computer Device
title_full_unstemmed Design of Citrus Fruit Detection System Based on Mobile Platform and Edge Computer Device
title_short Design of Citrus Fruit Detection System Based on Mobile Platform and Edge Computer Device
title_sort design of citrus fruit detection system based on mobile platform and edge computer device
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747137/
https://www.ncbi.nlm.nih.gov/pubmed/35009602
http://dx.doi.org/10.3390/s22010059
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