Comparing the accuracy of artificial intelligence models to detect alcohol in video images

Automated artificial intelligence (AI) models appear to be able to detect alcohol imagery in videos at large scale with high accuracy and in near real time. Of the three AI models tested, ZSL-LLaVA achieved the best balance between accuracy and speed. Offering a cost- and time-efficient alternative to labour-intensive manual coding, ZSL-LLaVA could be used to monitor alcohol-related visual content in videos across diverse media platforms.

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Publication Details

Journal
Addiction
Published
2026-01-26
DOI
https://doi.org/10.1111/add.70337
Citations
1
Primary Topic
Substance Abuse Treatment and Outcomes
Type
article
Field-Weighted Citation Impact
31.52
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article

Comparing the accuracy of artificial intelligence models to detect alcohol in video images

Joshua Millward, Emmanuel Kuntsche, Benjamin Riordan, Samatha Pararath et al.
1 citations
Addiction
Substance Abuse Treatment and Outcomes
31.52
article

Comparing the accuracy of artificial intelligence models to detect alcohol in video images

Joshua Millward, Emmanuel Kuntsche, Benjamin Riordan, Samatha Pararath, Zhen He
article en
1 citations

Abstract

Automated artificial intelligence (AI) models appear to be able to detect alcohol imagery in videos at large scale with high accuracy and in near real time. Of the three AI models tested, ZSL-LLaVA achieved the best balance between accuracy and speed. Offering a cost- and time-efficient alternative to labour-intensive manual coding, ZSL-LLaVA could be used to monitor alcohol-related visual content in videos across diverse media platforms.

Addiction
La Trobe University (AU)
Openalex Percentile: Top 1%
Substance Abuse Treatment and Outcomes
31.52
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