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Title
Preprocessing Taste Data for Deep Neural Networks
Issued Date
2023-10-12
Citation
Lee, Hyunjong. (2023-10-12). Preprocessing Taste Data for Deep Neural Networks. International Conference on Information and Communication Technology Convergence, ICTC 2023, 526–528. doi: 10.1109/ICTC58733.2023.10393201
Type
Conference Paper
ISBN
9798350313277
ISSN
2162-1241
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. © 2023 IEEE.
URI
http://hdl.handle.net/20.500.11750/47987
DOI
10.1109/ICTC58733.2023.10393201
Publisher
한국통신학회 (The Korean Institute of Communications and Information Sciences, KICS)
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Kwak, Jeongho곽정호

Department of Electrical Engineering and Computer Science

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