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2021 | OriginalPaper | Chapter

YOLOv5 versus YOLOv3 for Apple Detection

Authors : Anna Kuznetsova, Tatiana Maleva, Vladimir Soloviev

Published in: Cyber-Physical Systems: Modelling and Intelligent Control

Publisher: Springer International Publishing

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Abstract

The use of the YOLOv3 and YOLOv5 algorithms for apple detection in fruit-harvesting robots are compared. It is shown that the YOLOv5 algorithm could detect apples in orchards without additional pre- and post-processing with 97.8% Recall (fruit detection rate), and 3.5% False Positive Rate (FPR). It is much better than YOLOv3 that gives 90.8% Recall and 7.8 FPR when combined with special pre- and post-processing procedures, and then 9.1% Recall and 10.0% FPR without pre- and post-processing.

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previous chapter Statistical Precision-Recall Curves for Object Detection Algorithms Performance Measurement

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Title: YOLOv5 versus YOLOv3 for Apple Detection
Authors: Anna Kuznetsova
Tatiana Maleva
Vladimir Soloviev
Publisher: Springer International Publishing
Book: Cyber-Physical Systems: Modelling and Intelligent Control
Print ISBN: 978-3-030-66076-5

Electronic ISBN: 978-3-030-66077-2

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-66077-2_28

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