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Updated: Aug 11, 2025

Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
Images of Australian alcoholic and non-alcoholic beverages: A validation dataset
Poppy Watson1, Sandersan Onie2
1School of Psychology, Faculty of Science, UNSW Sydney, Sydney, New South Wales 2052, Australia.
Abstract:
For multi-session alcohol cognitive bias modification, a large image dataset depicting both alcohol and non-alcoholic beverages is required. We photographed a wide range of beverages and then validated them in a group of Australian community participants: 47 women and 39 men, aged from 18 to 73, who drank alcohol at least occasionally in the last year, with Alcohol Use Disorder Identification Test (AUDIT) scores ranging from 1 to 33. Participants were asked to categorize images as alcoholic vs non-alcoholic, rate the familiarity of each beverage and rate their craving for each beverage. The dataset includes all images and ratings for each image, stratified by gender and high/low AUDIT scores. Mean ratings per participant per beverage category are also provided.
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