X-ray tomography is a powerful tool that enables scientists and engineers to peer inside of objects in 3D, including computer ...
Monitoring forest health typically relies on remote sensing tools such as light detection and ranging (LiDAR), radar, and ...
Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data
DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...
Monitoring forest health typically relies on remote sensing tools such as light detection and ranging (LiDAR), radar, and ...
Abstract: Accurate fault diagnosis of trolley mechanisms in ship-to-shore cranes is essential for ensuring cargo transportation at ports. While deep neural networks (DNNs) have made some achievements ...
To explain how a convolutional neural network (CNN) processes an image, it is common to generate classification activation maps (CAMs) to reveal image areas that are relevant to output. Nevertheless, ...
ABSTRACT: AI techniques are proving unbeatable in the fight for supremacy in methods of evaluation, optimization, control, object recognition, sensor monitoring, image interpretation, machine learning ...
In this series of articles, I am looking at how to monitor my home/home lab LAN. In my first article, I probed my network to see what devices were on it and where they were located. In my next article ...
Picture yourself printing out this post to read later. Imagine the place you will sit while reading it. What do you see on the walls? What background sounds are in the room? Feel the weight and ...
Last Monday marked the beginning of Love Data Week, hosted by the Connolly Alexander Institute for Data Science in conjunction with the Tulane University Libraries. Love Data Week featured lectures, ...
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