  This paper has proposed a novel approach to classify the subjects' smoking
behavior by extracting relevant regions from a given image using deep learning.
After the classification, we have proposed a conditional detection module based
on Yolo-v3, which improves model's performance and reduces its complexity. As
per the best of our knowledge, we are the first to work on this dataset. This
dataset contains a total of 2,400 images that include smokers and non-smokers
equally in various environmental settings. We have evaluated the proposed
approach's performance using quantitative and qualitative measures, which
confirms its effectiveness in challenging situations. The proposed approach has
achieved a classification accuracy of 96.74% on this dataset.
