articleAgronomyJan 26, 2022GOLD OA

Automatic Bunch Detection in White Grape Varieties Using YOLOv3, YOLOv4, and YOLOv5 Deep Learning Algorithms

University of Padua · University of Udine

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Abstract

Over the last few years, several Convolutional Neural Networks for object detection have been proposed, characterised by different accuracy and speed. In viticulture, yield estimation and prediction is used for efficient crop management, taking advantage of precision viticulture techniques. Convolutional Neural Networks for object detection represent an alternative methodology for grape yield estimation, which usually relies on manual harvesting of sample plants. In this paper, six versions of the You Only Look Once (YOLO) object detection algorithm (YOLOv3, YOLOv3-tiny, YOLOv4, YOLOv4-tiny, YOLOv5x, and YOLOv5s) were evaluated for real-time bunch detection and counting in grapes. White grape varieties were…

Citation impact

239
total citations
FWCI
47.24
Percentile
100%
References
58
Citations per year

Authors

5

Topics & keywords

Keywords
  • Convolutional neural network
  • Object detection
  • Computer science
  • Artificial intelligence
  • Pattern recognition (psychology)
  • Deep learning
UN Sustainable Development Goals
  • Zero hunger
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