Comparison of machine learning and deep learning models for the assessment of rondo wine grape quality with a hyperspectral camera-Reference-Cited by-同舟云学术

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Comparison of machine learning and deep learning models for the assessment of rondo wine grape quality with a hyperspectral camera

Published:2024-08 Issue: Volume:8 Page:100474
ISSN:2772-3755
Container-title:Smart Agricultural Technology
language:en
Short-container-title:Smart Agricultural Technology

Author:

Swe Khin Nilar^ORCID,Noguchi Noboru

Funder

Hokkaido University

Publisher

Elsevier BV

Reference23 articles.

1. Determination of sugar content in whole Port wine grape berries combining hyperspectral imaging with neural networks methodologies;Gomes,2014

2. A review of different dimensionality reduction methods for theprediction of sugar content from hyperspectral images of wine grape berries;Silva;Appl. Soft Comput.,2021

3. Predicting the anthocyanin content of wine grapes by NIR hyperspectral imaging;Chen;Food Chem.,2015

4. Brix, pH and anthocyanin content determination in whole Port wine grape berries by hyperspectral imaging and neural networks;Fernandes;Comput. Electron. Agric.,2015

5. Characterization of neural network generalization in the determination of pH and anthocyanin content of wine grape in new vintages and varieties;Gomes;Food Chem.,2017

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