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 ...

Abstract: Accurate electricity consumption forecasting is essential for effective power management, especially in the presence of unpredictable events that disrupt typical consumption patterns. Using ...

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: 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, ...

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

Abstract: The cloud-edge-terminal architecture relies on hierarchy for resource allocation but lacks global optimization. The computing power network (CPN) introduces a new distributed computing ...

Abstract: Wrist trauma and even fractures occur frequently in daily life, particularly among children who account for a significant proportion of fracture cases. Before performing surgery, surgeons ...

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 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 ...