Abstract: Ultra-wideband (UWB) technology, with its strong penetration capability and high time resolution, has become a popular wireless positioning method widely used in fields such as smart home, ...
Abstract: To address the challenges of road segmentation in remote sensing images—such as elongated structures, blurred boundaries, and the high cost of manual annotations—we propose a semi-supervised ...
The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...
US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...
ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
Supervised learning relies on historical, labeled data to train algorithms for specific outcomes. This approach is widely used in the financial sector, where reliable past data can guide future ...
This week I interviewed Senator Amy Klobuchar, Democrat of Minnesota, about her Preventing Algorithmic Collusion Act. If you don’t know what algorithmic collusion is, it’s time to get educated, ...
The identification of cell types in complex tissues is an important step in research into cellular heterogeneity in disease. We present a linear fast semi-supervised clustering (LFSC) algorithm that ...
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