This study delves into the application of Electroencephalogram (EEG)-based techniques for emotion and consciousness recognition, focusing on disorders of consciousness (DOC). By evaluating existing approaches in terms...
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In systems based on pattern recognition using surface electromyography (sEMG) signals, there exists a problem of electrode shift during the process of donning and doffing. Directly using models trained on the source d...
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In the field of autonomous driving, drifting control is of great importance for driving safety to deal with extreme situations. In order to better control the unmanned vehicle, it is necessary to have high-precision a...
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The lack of communication options for Deaf and hearing people, some may say creates a significant social disadvantage in accessing the often-bare essential services. In contrast to acoustically communicated sound patt...
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With the development of smart handheld devices and location technology, users can use location-based services (LBS) to search for nearby friends and strangers to enjoy a better social experience. However, the disclosu...
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Cyber-Physical Systems represent a fusion of spatially distributed digital and physical elements. Due to the increased complexity of such systems, understanding their holistic operational conditions becomes more and m...
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Deep learning, a cutting-edge approach of machine learning, surpasses classical machine learning when it comes to detecting particular structures in complicated, high-dimensional data in the area of computer vision. T...
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Detecting faces and fingerprints within images serves as a pivotal component in multiple computer vision applications. These applications encompass but are not limited to face recognition, facial expression analysis, ...
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In traditional direct torque control of permanent magnet synchronous motors, the flux reference is typically set to a constant value. However, the optimal flux reference varies depending on motor parameters and operat...
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In this paper, based on compressed sensing and neural networks, we present an intelligent sparse channel estimation technique for Massive MIMO systems. We show that our approach improves considerably the estimation ac...
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