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Extracting the height of lettuce by using neural networks of image recognition in deep learning
  • Xiyue Guo,
  • Minjuan Wang
Xiyue Guo
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Minjuan Wang

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The traditional method of measuring the lettuce height is a manual measurement with instruments, which is greatly affected by human error.At present, researchers have proposed to use color cameras to obtain RGB images of lettuce, and to obtain the height of lettuce from the images. However, these tasks usually require camera calibration or a reference object with a known height, which is somewhat restrictive. Considering that deep neural networks have a powerful ability to feature extraction and expression, without camera calibration and reference objects, we try to use four networks of image recognition to explore the effect of deep learning on abstracting the lettuce height from RGB images. On the test set, including 80 images and height from 0.9 cm to 7.5 cm, we achieve a good result with a mean absolute error of 1.22 mm.