smoking Computer Vision Project
Updated 2 years ago
128
6
Here are a few use cases for this project:
-
Anti-Counterfeiting Operations: The model can be used by anti-smuggling and anti-counterfeiting agencies to identify and verify cigarette brands in images or video feeds. This could help in distinguishing between genuine and counterfeit products.
-
Retail Inventory Management: Retail shops dealing with cigarettes can use the model to automate their inventory management systems. The model will be able to recognize and classify different cigarette brands from the surveillance footage or images taken for inventory purposes.
-
Advertisements and Media Regulations: Regulatory authorities can use this model to monitor and enforce regulations related to tobacco advertising and promotions on media channels. The model would identify specific cigarette brands in the content, helping authorities to ensure compliance with the rules.
-
Online Retail: E-commerce platforms selling cigarettes can use the model to automatically tag products in pictures, thus improving the searchability and categorization of products on their platforms.
-
Public Health Surveillance: Health organizations and research institutions can use the model for studies related to smoking, such as monitoring and evaluating the prevalence of specific cigarette brands in different regions or demographic groups. This could contribute to research on smoking habits and inform public health strategies.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
smoking-4z420_dataset,
title = { smoking Dataset },
type = { Open Source Dataset },
author = { seg },
howpublished = { \url{ https://universe.roboflow.com/seg-zlmdp/smoking-4z420 } },
url = { https://universe.roboflow.com/seg-zlmdp/smoking-4z420 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { sep },
note = { visited on 2024-11-17 },
}