Region extraction based approach for cigarette usage classification using deep learning

• URL: http://arxiv.org/abs/2103.12523v1
• Date: Tue, 23 Mar 2021 13:19:43 GMT
• Title: Region extraction based approach for cigarette usage classification using deep learning
• Authors: Anshul Pundhir, Deepak Verma, Puneet Kumar, Balasubramanian Raman
• Abstract summary: We have 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. The proposed approach has achieved a classification accuracy of 96.74% on this dataset.
• Score: 15.387646343210337
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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