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arXiv · 2104.09808

Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning

Leon Amadeus Varga·Jan Makowski·Andreas Zell
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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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Leon Amadeus Varga, Jan Makowski, Andreas Zell. 2021-04-20. Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning. https://arxiv.org/abs/2104.09808

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