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recognition algorithms » reconstruction algorithms (Expand Search)
process recognition » process cognition (Expand Search), precise recognition (Expand Search), proton recognition (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
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binary data » primary data (Expand Search), dietary data (Expand Search)
fast model » first model (Expand Search), rat model (Expand Search), best model (Expand Search)
recognition algorithms » reconstruction algorithms (Expand Search)
process recognition » process cognition (Expand Search), precise recognition (Expand Search), proton recognition (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary fast » binary mask (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
fast model » first model (Expand Search), rat model (Expand Search), best model (Expand Search)
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Bayesian sequential design for sensitivity experiments with hybrid responses
Published 2023“…To deal with the problem of complex computation involved in searching for optimal designs, fast algorithms are presented using two strategies to approximate the optimal criterion, denoted as SI-optimal design and Bayesian D-optimal design, respectively. …”
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Data Sheet 1_Advances and prospects in reconstruction approaches for snow cover mapping using polar-orbiting satellites.docx
Published 2025“…<p>Snow cover is recognized as one of the most variable land cover parameters and plays a critical role in the global energy balance, climate change, and hydrological processes. Polar-orbiting satellites serve as the primary data source for monitoring both polar and global snow cover, providing wide coverage and high spatial resolution products. …”