Indigenous food recognition model based on various convolutional neural network architectures for gastronomic tourism business analytics

Indigenous food recognition model based on various convolutional neural network architectures for gastronomic tourism business analytics

In gastronomic tourism, food is viewed as the central tourist attraction. Specifically, indigenous food is known to represent the expression of local culture and identity. To promote gastronomic tourism, it is critical to have a model for the food business analytics system. This research undertakes...

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Bibliographic Details
Main Authors: Hanapi, R. (Author), Hashem, I.A.T (Author), Hou, C.J (Author), Mohamed, R. (Author), Moung, E.G (Author), Razali, M.N (Author), Yahya, F. (Author)
Format: Article
Language:English
Published: MDPI AG 2021
Series:Information (Switzerland)
Subjects:
Advanced Analytics
Business analytics
Classification (of information)
Classification accuracy
CNN
Computational speed
Convolution
Convolutional neural networks
Deep learning
Empirical evaluations
Feature representation
Food features
Food recognition
Food sentiment
Gastronomic tourism
Leisure industry
Network architecture
Performance drawback
Silicon compounds
Tourism
Tourist attractions
Transfer learning
Web application systems
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