Optimization of number of wireless temperature sensors using clustering algorithm for deep learning algorithm-based Kimchi quality prediction-Reference-Cited by-同舟云学术

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Optimization of number of wireless temperature sensors using clustering algorithm for deep learning algorithm-based Kimchi quality prediction

Published:2024-04 Issue: Volume:367 Page:111883
ISSN:0260-8774
Container-title:Journal of Food Engineering
language:en
Short-container-title:Journal of Food Engineering

Author:

Kim Tae Hyong^ORCID,Kim Ji Young,Kim Jong Hoon,Oh Seung Eel^ORCID

Funder

Korea Food Research Institute

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Food Science

Reference42 articles.

1. Clustering and classification for time series data in visual analytics: a survey;Ali;IEEE Access,2019

2. Integration of RFID, wireless sensor networks, and data mining in an e-pedigree food traceability system;Alfian;J. Food Eng.,2017

3. Deep time-series clustering: a review;Alqahtani;Electronics,2021

4. Freshness indicator for monitoring changes in quality of packaged kimchi during storage;Baek;Food Packag. Shelf Life,2020

5. Eggshell crack detection using deep convolutional neural networks;Botta;J. Food Eng.,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prediction of Teaching Quality of Open Online Courses based on Weighted Markov Chain;Proceedings of the 2024 9th International Conference on Distance Education and Learning;2024-06-14

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