Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning

Code

• github.com/cogsys-tuebingen/deephs_fruit
  OfficialIn paperpytorch★ 64

Abstract

We present a system to measure the ripeness of fruit with a hyperspectral camera and a suitable deep neural network architecture. This architecture did outperform competitive baseline models on the prediction of the ripeness state of fruit. For this, we recorded a data set of ripening avocados and kiwis, which we make public. We also describe the process of data collection in a manner that the adaption for other fruit is easy. The trained network is validated empirically, and we investigate the trained features. Furthermore, a technique is introduced to visualize the ripening process.

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Reproductions