Narit Hnoohom1, Sakorn Mekruksavanich2, Anuchit Jitpattanakul3,4,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1245-1259, 2023, DOI:10.32604/iasc.2023.028290
Abstract Smoking is a major cause of cancer, heart disease and other afflictions that lead to early mortality. An effective smoking classification mechanism that provides insights into individual smoking habits would assist in implementing addiction treatment initiatives. Smoking activities often accompany other activities such as drinking or eating. Consequently, smoking activity recognition can be a challenging topic in human activity recognition (HAR). A deep learning framework for smoking activity recognition (SAR) employing smartwatch sensors was proposed together with a deep residual network combined with squeeze-and-excitation modules (ResNetSE) to increase the effectiveness of the SAR framework. The proposed model was tested against… More >
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