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FOODITY Practice Abstract no. 1: Food and nutrition components – Food recognition from photos

FOODITY Practice Abstract no. 2: Food and nutrition components – Food product identification from photo

FOODITY Practice Abstract no. 3: Food and nutrition component – Personalised nutrition plan

FOODITY Practice Abstract no. 4: Food and nutrition component – Personalised support for nutrition/physical activity

FOODITY Practice Abstract no. 5: Food and nutrition component – Nutrition and activity ontology

FOODITY Practice Abstract no. 6: Nutrition recommendation systems

FOODITY Practice Abstract no. 7: Recipe recommendation systems

FOODITY Practice Abstract no. 8: Restaurant recommendation systems

FOODITY Practice Abstract no. 9: Data collection technologies for food, nutrition, and health

FOODITY Practice Abstract no. 10: Online food retail

FOODITY Practice Abstract no. 11: Food and nutrition datasets

FOODITY Practice Abstract no. 12: Food and nutrition standards

FOODITY Practice Abstract no. 13: Food and nutrition data ontologies Creators

FOODITY Practice Abstract no. 14: dataU – A GDPR compliant cloud-based distributed platform

FOODITY Practice Abstract no. 15: Data lake – Food and nutrition data repository Creators

FOODITY Practice Abstract no. 16: Photovoice Methodology

FOODITY Practice Abstract no. 17: Photovoice workshop results – Austria hub

FOODITY Practice Abstract no. 18: Photovoice workshop results – Bulgaria hub

FOODITY Practice Abstract no. 19: Photovoice workshop results – Portugal hub

FOODITY Practice Abstract no. 20: FOODITY – Open Call #1 project – EcoTrace

FOODITY Practice Abstract no. 21: FOODITY – Open Call #1 project – CSE-TKAS

FOODITY Practice Abstract no. 22: FOODITY – Open Call #1 project – DIAITA

FOODITY Practice Abstract no. 23: FOODITY – Open Call #1 project – MI4SaferFOOD

FOODITY Practice Abstract no. 24: FOODITY – Open Call #1 project – STRADA

FOODITY Practice Abstract no. 25: FOODITY – Open Call #1 project – FoodMarketMap

Publications

Artificial Intelligence and Machine Learning Technologies for Personalized Nutrition: A Review

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