How much are we exposed to alcohol in electronic media? Development of the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA).

Journal: Drug and alcohol dependence

PMID: 31954949

Abstract

BACKGROUND: Evidence demonstrates that seeing alcoholic beverages in electronic media increases alcohol initiation and frequent and excessive drinking, particularly among young people. To efficiently assess this exposure, the aim was to develop the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA) to automatically identify beer, wine and champagne/sparkling wine from images.

Authors

Emmanuel Kuntsche

Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia. Electronic address: e.kuntsche@latrobe.edu.au.
Abraham Albert Bonela

Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia; Department of Computer Science and Information Technology, La Trobe University, Melbourne, Australia.
Gabriel Caluzzi

Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia.
Mia Miller

Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia.
Zhen He

Keywords

Adolescent Adult Alcohol Drinking Alcoholic Beverages Algorithms Beer Deep Learning Female Humans Male Mass Media Pattern Recognition, Automated Reproducibility of Results Wine

External Resources

View on PubMed Access via DOI PubMed (31954949)

How much are we exposed to alcohol in electronic media? Development of the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA).

Abstract

Authors

Keywords

External Resources

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