Abstract: With the continuous development of intelligent UAV technology, efficient and accurate sensing of surrounding objects through onboard sensors has become an important research direction. Among ...
Abstract: Deep learning has garnered extensive attention in hyperspectral image (HSI) processing. However, its application in HSI semantic segmentation tasks has been relatively limited. Although ...
Abstract: In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled method for jointly learning deep latent-variable models ...
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 ...
Abstract: The iterative hard thresholding (IHT) algorithm is widely used for recovering sparse signals in compressed sensing. Despite the development of numerous variants of this effective algorithm, ...
Abstract: Recent studies have shown that the deep domain adaptation (DA) technique has achieved remarkable results in cross-domain hyperspectral image (HSI) classification task. However, these DA ...
Abstract: This article simultaneously addresses the dual-rate and view constraints issues for the image-based visual servoing (IBVS) system of robot manipulators. Considering the low sampling ...
Abstract: Considerable interindividual variability exists in electroencephalogram (EEG) signals, resulting in challenges for subject-independent emotion recognition tasks. Current research in ...
Abstract: A node in a social network is not part of just a cohesive group; it may be classified in many close or different communities. The community detection problem in social networks is similar to ...
Abstract: This brief presents a 12-bit low-power successive-approximation-register (SAR) capacitance-to-digital converter (CDC) for capacitive pressure sensors. It adopts a capacitance-to-voltage ...
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 ...