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 ...
Forests hide critical ecological information beneath dense canopy layers, where traditional imaging techniques struggle to access.
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, ...
This repository documents my complete learning journey through the Coursera course Remote Sensing Image Acquisition, Analysis, and Applications. It is part of my broader PhD preparation plan in ...
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 ...
Neural processing unts (NPUs) are the latest chips you might find in smartphones and laptops — but what are they ard why are they so important? When you purchase through links on our site, we may earn ...
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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