Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At the ...
Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified ...
Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...
A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
No audio available for this content. High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, ...
Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
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