Hao Yu (National University of Defense Technology), Chuan Ma (Chongqing University), Xinhang Wan (National University of Defense Technology), Jun Wang (National University of Defense Technology), Tao ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Add Yahoo as a preferred source to see more of our stories on Google. Members of law enforcement work the scene following a suspected shooting by an ICE agent during federal law enforcement operations ...

The recent past has seen an increasing interest in Heterogeneous Graph Neural Networks (HGNNs), since many real-world graphs are heterogeneous in nature, from citation graphs to email graphs. However, ...

Deep dive into the AlexNet architecture, one of the pioneering convolutional neural networks in computer vision. #AlexNet #DeepLearning #CNN House Republicans aren’t having any fun Russia-Ukraine war: ...

It was a relatively brief segment, but Fox News made a significant break with reality this week. The cable news giant seemingly revived its retired “We report, you decide” slogan during a bizarre ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...

Introduction: Segmentation of echocardiograms plays a crucial role in clinical diagnosis. Beyond accuracy, a major challenge of video echocardiogram analysis is the temporal consistency of consecutive ...

Abstract: Developing effective and accurate methods for automatic estimation of pain level is vital, particularly for monitoring individuals, such as newborns and patients in intensive care units, who ...

Abstract: The rapid increase in multimodal data (text, audio, and video) has enhanced consumer applications, such as sentiment analysis, emotion detection, and content retrieval. However, the ...