Forecasting temperature in fresh-cut vegetables and fruits using an autoencoder and deep neural network

Authors

Yosuke Matsuo (ORCID: https://orcid.org/0000-0002-6462-9727)
Takahiro Orikasa (ORCID: https://orcid.org/0000-0002-5853-3446)
Shoji Koide (ORCID: https://orcid.org/0000-0002-5898-9558)
Satoshi Kawamura (ORCID: https://orcid.org/0000-0003-1140-2470)

Institutions

Iwate University (JP)

Publication Details

Journal: Nippon Shokuhin Kagaku Kogaku Kaishi
Published: 2025-09-30
DOI: https://doi.org/10.3136/nskkk.nskkk-d-25-00040
Primary Topic: Advanced Chemical Sensor Technologies
Type: article
Field-Weighted Citation Impact: 0.00

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article

Forecasting temperature in fresh-cut vegetables and fruits using an autoencoder and deep neural network

Yosuke Matsuo, Takahiro Orikasa, Shoji Koide, Satoshi Kawamura

Sep 30, 2025

Nippon Shokuhin Kagaku Kogaku Kaishi

Advanced Chemical Sensor Technologies

article

Forecasting temperature in fresh-cut vegetables and fruits using an autoencoder and deep neural network

Yosuke Matsuo, Takahiro Orikasa, Shoji Koide, Satoshi Kawamura

September 30, 2025article en

Abstract

No abstract available for this paper.

Nippon Shokuhin Kagaku Kogaku KaishiVol. 73(2)

Iwate University (JP)

Openalex Percentile: Top 74%

Advanced Chemical Sensor Technologies

DOI Source OpenAlex

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Forecasting temperature in fresh-cut vegetables and fruits using an autoencoder and deep neural network — Yosuke Matsuo, Takahiro Orikasa, et al. · Nippon Shokuhin Kagaku Kogaku Kaishi (2025) | TGRS Research Map | TGRS