Preprocessing Taste Data for Deep Neural Networks

Hyunjong Lee; Han Hee Jung; Jeongho Kwak; Junwoo Yea; Jihwan P. Choi; Kyung In Jang

doi:10.1109/ICTC58733.2023.10393201

Preprocessing Taste Data for Deep Neural Networks

Hyunjong Lee, Han Hee Jung, Jeongho Kwak, Junwoo Yea, Jihwan P. Choi, Kyung In Jang

Daegu Gyeongbuk Institute of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Analyzing wine using taste data is a promising field due to the explosive expansion of online commerce. However, because of the wide variety of wine types with different flavors and aromas, it is difficult for consumers to choose the wine that suits their taste, and also difficult for sellers to recommend appropriate wines to consumers. Therefore, it is necessary to numerically analyze and classify wine, and a deep learning algorithm which mimics the human brain is appropriate for analyzing the wine data [1]. In this paper, we introduce several studies of wine classification using deep learning architectures and propose preprocessing methods for applying the taste data of wine to deep learning networks.

Original language	English
Title of host publication	ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence
Subtitle of host publication	Exploring the Frontiers of ICT Innovation
Publisher	IEEE Computer Society
Pages	526-528
Number of pages	3
ISBN (Electronic)	9798350313277
DOIs	https://doi.org/10.1109/ICTC58733.2023.10393201
State	Published - 2023
Event	14th International Conference on Information and Communication Technology Convergence, ICTC 2023 - Jeju Island, Korea, Republic of Duration: 11 Oct 2023 → 13 Oct 2023

Publication series

Name	International Conference on ICT Convergence
ISSN (Print)	2162-1233
ISSN (Electronic)	2162-1241

Conference

Conference	14th International Conference on Information and Communication Technology Convergence, ICTC 2023
Country/Territory	Korea, Republic of
City	Jeju Island
Period	11/10/23 → 13/10/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

data augmentation
deep learning
preprocessing
taste classification
taste sensor
wine

Access to Document

10.1109/ICTC58733.2023.10393201

Cite this

Lee, H., Jung, H. H., Kwak, J., Yea, J., Choi, J. P., & Jang, K. I. (2023). Preprocessing Taste Data for Deep Neural Networks. In ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation (pp. 526-528). (International Conference on ICT Convergence). IEEE Computer Society. https://doi.org/10.1109/ICTC58733.2023.10393201

@inproceedings{d5f33da8fbba4c17b8aad489919e9b7b,

title = "Preprocessing Taste Data for Deep Neural Networks",

abstract = "Analyzing wine using taste data is a promising field due to the explosive expansion of online commerce. However, because of the wide variety of wine types with different flavors and aromas, it is difficult for consumers to choose the wine that suits their taste, and also difficult for sellers to recommend appropriate wines to consumers. Therefore, it is necessary to numerically analyze and classify wine, and a deep learning algorithm which mimics the human brain is appropriate for analyzing the wine data [1]. In this paper, we introduce several studies of wine classification using deep learning architectures and propose preprocessing methods for applying the taste data of wine to deep learning networks.",

keywords = "data augmentation, deep learning, preprocessing, taste classification, taste sensor, wine",

author = "Hyunjong Lee and Jung, {Han Hee} and Jeongho Kwak and Junwoo Yea and Choi, {Jihwan P.} and Jang, {Kyung In}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 14th International Conference on Information and Communication Technology Convergence, ICTC 2023 ; Conference date: 11-10-2023 Through 13-10-2023",

year = "2023",

doi = "10.1109/ICTC58733.2023.10393201",

language = "English",

series = "International Conference on ICT Convergence",

publisher = "IEEE Computer Society",

pages = "526--528",

booktitle = "ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence",

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Lee, H, Jung, HH, Kwak, J, Yea, J, Choi, JP & Jang, KI 2023, Preprocessing Taste Data for Deep Neural Networks. in ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation. International Conference on ICT Convergence, IEEE Computer Society, pp. 526-528, 14th International Conference on Information and Communication Technology Convergence, ICTC 2023, Jeju Island, Korea, Republic of, 11/10/23. https://doi.org/10.1109/ICTC58733.2023.10393201

Preprocessing Taste Data for Deep Neural Networks. / Lee, Hyunjong; Jung, Han Hee; Kwak, Jeongho et al.
ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation. IEEE Computer Society, 2023. p. 526-528 (International Conference on ICT Convergence).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Preprocessing Taste Data for Deep Neural Networks

AU - Lee, Hyunjong

AU - Jung, Han Hee

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AU - Yea, Junwoo

AU - Choi, Jihwan P.

AU - Jang, Kyung In

PY - 2023

Y1 - 2023

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AB - Analyzing wine using taste data is a promising field due to the explosive expansion of online commerce. However, because of the wide variety of wine types with different flavors and aromas, it is difficult for consumers to choose the wine that suits their taste, and also difficult for sellers to recommend appropriate wines to consumers. Therefore, it is necessary to numerically analyze and classify wine, and a deep learning algorithm which mimics the human brain is appropriate for analyzing the wine data [1]. In this paper, we introduce several studies of wine classification using deep learning architectures and propose preprocessing methods for applying the taste data of wine to deep learning networks.

KW - data augmentation

KW - deep learning

KW - preprocessing

KW - taste classification

KW - taste sensor

KW - wine

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M3 - Conference contribution

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T3 - International Conference on ICT Convergence

SP - 526

EP - 528

BT - ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence

PB - IEEE Computer Society

T2 - 14th International Conference on Information and Communication Technology Convergence, ICTC 2023

Y2 - 11 October 2023 through 13 October 2023

ER -

Preprocessing Taste Data for Deep Neural Networks

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Keywords

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