The rapid progress in digitalization and automation have led to an accelerated growth in
healthcare, generating novel models that are creating new channels for rendering treatment …

Abstract Human Action Recognition (HAR) involves human activity monitoring task in
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …

Along with the massive growth of the Internet from the 1990s until now, various innovative
technologies have been created to bring users breathtaking experiences with more virtual …

Human action recognition systems use data collected from a wide range of sensors to
accurately identify and interpret human actions. One of the most challenging issues for …

This letter proposes a cost-efficient convolutional neural network (CNN) for robust automatic
modulation classification (AMC) deployed for cognitive radio services of modern …

Action recognition based on skeleton key joints has gained popularity due to its cost
effectiveness and low complexity. Existing Convolutional Neural Network (CNN) based …

This paper proposes a convolutional neural network (CNN), called SCGNet, for low-
complexity and robust modulation recognition in intelligent communication receivers …

Action recognition is a major branch of computer vision research. As a widely used
technology, action recognition has been applied to human–computer interaction, intelligent …

Mixed reality environments give better chances to provide constant help to the people in
need. Applied there artificial intelligence models will provide ad hoc monitoring measures …

Abstract Human Action Recognition (HAR) has remained one of the most challenging tasks
in computer vision. With the surge in data-driven methodologies, the depth modality has …