Smoking Detection in Video

P. Sumalatha, Gurram Soumya and Angaluri Yashaswini Tapathi

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2023, vol. 9, issue 3, 177-182

Abstract: This paper presents a novel approach for identifying smoking behavior using deep learning to extract important features from an image. The approach involves using deep learning to identify key regions in an image and a conditional detection system built using YOLOv5 to improve performance and simplify the model. The method was tested on a dataset containing 7,000 images with equal representation of smokers and non-smokers in various settings. The effectiveness of the technique was evaluated using both quantitative and qualitative measures, resulting in a classification accuracy of 96.74% on the dataset.

Keywords: Deep Learning; YOLOv5; Quantitative Measures; Qualitative Measures. (search for similar items in EconPapers)
Date: 2023
Note: Article URL: https://ijsrcseit.com/CSEIT2390339
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