Computer Vision Models for Detecting Large Cigars on Social Media
This computer vision model offers a novel and scalable approach to tobacco monitoring by automatically detecting large cigars in social media content. Its application may enhance the efficiency of product identification and facilitate research on use patterns, user perceptions, and emerging marketing strategies, thereby generating evidence to inform regulatory decision-making and policies aimed at preventing initiation.
Authors
- Rachel R. Ouellette (ORCID: https://orcid.org/0000-0001-6982-0830)
- Dhiraj Murthy (ORCID: https://orcid.org/0000-0001-9734-1124)
- Grace Kong (ORCID: https://orcid.org/0000-0002-9269-3435)
- Shuvam Keshari (ORCID: https://orcid.org/0009-0009-4819-6720)
- Juhan Lee (ORCID: https://orcid.org/0000-0003-0860-3327)
Institutions
- Albert Einstein College of Medicine (US)
- Danish School of Media and Journalism (DK)
- Yale University (US)
- The University of Texas at Austin (US)
Publication Details
- Journal
- Nicotine & Tobacco Research
- Published
- 2025-10-13
- DOI
- https://doi.org/10.1093/ntr/ntaf206
- Primary Topic
- Smoking Behavior and Cessation
- Type
- article
- Field-Weighted Citation Impact
- 0.00