Conference paper Open Access
AI in gastronomic tourism
Pavlidis, George;
Markantonatou, Stella;
Toraki, Katerina;
Vacalopoulou, Anna;
Strouthopoulos, Charalampos;
Varsamis, Dimitrios;
Tsimpiris, Alkiviadis;
Mouroutsos, Spyridon;
Kiourt, Chairi;
Sevetlidis, Vasileios;
Minos, Panagiotis
Gastronomy is increasingly becoming a decisive flavour of tourists’ experience. Tourists’ gastronomic experience could be significantly enhanced by AI tools that provide image-based dish recognition and menu translation, thus covering the basic needs of tourists during a visit that involves culinary experiences. This paper presents and discusses solutions explored with the project GRE-Taste that deals with the enhancement of culinary tourism experience in northern Greece, for which no linguistic resources exist and where general-purpose tools fail.
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- Publication date:
- July 13, 2020
- DOI:
-
- ISBN:
- 978-84-09-21931-5
- Keyword(s):
- dish recognition menu translation gastronomic tourism artificial intelligence optical character recognition convolutional neural networks PureFoodNet
- Published in:
- Proceedings of the 2nd International Conference on Advances in Signal Processing and Artificial Intelligence, International Frequency Sensor Association (IFSA) Publishing, S. L., pp. 168-174 (978-84-09-21931-5).
- Meeting:
- International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI), Berlin, Germany, 18-20 November 2020 (Session Keynotes)
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International