Ali Khan1,4, Somaiya Khan2, Bilal Hassan3, Rizwan Khan1,4, Zhonglong Zheng1,4,*
CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 403-424, 2023, DOI:10.32604/cmc.2023.040251
Abstract Smoking has an economic and environmental impact on society due to the toxic substances it emits. Convolutional Neural Networks (CNNs) need help describing low-level features and can miss important information. Moreover, accurate smoker detection is vital with minimum false alarms. To answer the issue, the researchers of this paper have turned to a self-attention mechanism inspired by the ViT, which has displayed state-of-the-art performance in the classification task. To effectively enforce the smoking prohibition in non-smoking locations, this work presents a Vision Transformer-inspired model called SmokerViT for detecting smokers. Moreover, this research utilizes a locally curated dataset of 1120 images… More >
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