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2021 | OriginalPaper | Chapter

Semantic Segmentation Using Convolutional Neural Networks for Volume Estimation of Native Potatoes at High Speed

Authors : Miguel Chicchón, Ronny Huerta

Published in: Information Management and Big Data

Publisher: Springer International Publishing

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Abstract

Peru is one of the main producers of a wide variety of native potatoes in the world. Nevertheless, to achieve a competitive export of derived products is necessary to implement automation tasks in the production process. Nowadays, volume measurements of native potatoes are done manually, increasing production costs. To reduce these costs, a deep approach based on convolutional neural networks have been developed, tested, and evaluated, using a portable machine vision system to improve high-speed native potato volume estimations. The system was tested under different conditions and was able to detect volume with up to 90% of accuracy.

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Title: Semantic Segmentation Using Convolutional Neural Networks for Volume Estimation of Native Potatoes at High Speed
Authors: Miguel Chicchón
Ronny Huerta
Publisher: Springer International Publishing
Book: Information Management and Big Data
Print ISBN: 978-3-030-76227-8

Electronic ISBN: 978-3-030-76228-5

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-76228-5_17

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