2026-10-14T01:44:53Z https://data.mendeley.com/oai

oai:data.mendeley.com/9ygs9vhnpw.1 2022-08-22T15:45:59Z

Bansal, Nikunj Allergen30 Mendeley Data Allergen30 is created with the goal of building a robust detection model that can assist people in avoiding possible allergic reactions. It contains images of 30 commonly used food items that can cause an adverse reaction within a human body. These food items pertain to specific food intolerances which can trigger an allergic reaction. Such food intolerance primarily includes Lactose, Histamine, Gluten, Salicylate, Caffeine, and Ovomucoid intolerance. The 30 food items (labels) in the dataset include 'alcohol', 'alcohol glass', 'almond', 'avocado', 'blackberry', 'blueberry', 'bread', 'bread loaf', 'capsicum', 'cheese', 'chocolate', 'cooked meat', 'dates', 'egg', 'eggplant', 'icecream', 'milk', 'milk based beverage', 'mushroom', 'non milk based beverage', 'pasta', 'pineapple', 'pistachio', 'pizza', 'raw meat', 'roti', 'spinach', 'strawberry', 'tomato' and 'whole egg boiled'. Object Detection Allergen Food Allergy Food Allergen Deep Learning Food Application of Computer Vision Sarkar, Tanmay Choudhury, Tanupriya Mishra, Mayank Dataset doi:10.17632/9ygs9vhnpw.1 oai:data.mendeley.com/9ygs9vhnpw.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/9ygs9vhnpw 2022-08-22T15:45:59Z