Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=7361 ...

Abstract: Building the next-generation wireless systems that could support services such as the metaverse, digital twins (DTs), and holographic teleportation is challenging to achieve exclusively ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6687316 ...

Abstract: Multiview subspace clustering (MSC) maximizes the utilization of complementary description information provided by multiview data and achieves impressive clustering performance. However, ...

Abstract: Change detection (CD) is an essential aspect of urban planning and resource management. Deep learning (DL) has the potential to detect complex changes from massive data more automatically ...

Abstract: Deep learning models have been widely investigated for computing and analyzing brain images across various downstream tasks such as disease diagnosis and age regression. Most existing models ...

Abstract: Considerable interindividual variability exists in electroencephalogram (EEG) signals, resulting in challenges for subject-independent emotion recognition tasks. Current research in ...

Abstract: Due to the wide existence of unlabeled graph-structured data (e.g. molecular structures), the graph-level clustering has recently attracted increasing attention, whose goal is to divide the ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=76 ...

Abstract: Velostat is a conductive material that can be used as sensing media for robotic tactile perception. However, the performance of the Velostat-based sensors is suppressed by its intrinsic ...

Abstract: In ultra-dense unmanned aerial vehicle (UAV) networks, it is challenging to coordinate the resource allocation and interference management among large-scale UAVs, for providing flexible and ...

Abstract: The adoption of voluntary environmental standards has emerged as a promising approach to coping with climate change and achieving sustainable development. While prior research has ...