Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning

• URL: http://arxiv.org/abs/2104.09808v1
• Date: Tue, 20 Apr 2021 07:43:19 GMT
• Title: Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning
• Authors: Leon Amadeus Varga, Jan Makowski and Andreas Zell
• Abstract summary: 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 state of ripeness.
• Score: 14.853897011640022
• License: http://creativecommons.org/licenses/by-sa/4.0/
• 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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