Search alternatives:
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
using optimization » joint optimization (Expand Search), design optimization (Expand Search), step optimization (Expand Search)
binary task » binary mask (Expand Search)
task using » tasks using (Expand Search), risk using (Expand Search)
binary ai » binary _ (Expand Search), binary pairs (Expand Search)
ai driven » _ driven (Expand Search), a driver (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
using optimization » joint optimization (Expand Search), design optimization (Expand Search), step optimization (Expand Search)
binary task » binary mask (Expand Search)
task using » tasks using (Expand Search), risk using (Expand Search)
binary ai » binary _ (Expand Search), binary pairs (Expand Search)
ai driven » _ driven (Expand Search), a driver (Expand Search)
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CDF of task latency, approximated as the inverse of the achieved computation rate.
Published 2025Subjects: -
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Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30.
Published 2025Subjects: -
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Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30.
Published 2025Subjects: -
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The Pseudo-Code of the IRBMO Algorithm.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. meta-heuristic algorithms boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. feature selection algorithm boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames.
Published 2025Subjects: -
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Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png
Published 2025“…</p>Methods<p>To address these challenges, we propose a novel AI-driven framework that incorporates two key methodological innovations: CardioSpectra, a structured sparse inference model, and Risk-Stratified Exertional Embedding (RSEE), a domain-specific representation learning strategy. …”
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