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models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
field optimization » lead optimization (Expand Search), guided optimization (Expand Search), linear optimization (Expand Search)
library based » laboratory based (Expand Search)
binary mask » binary image (Expand Search)
mask models » risk models (Expand Search), base models (Expand Search), asr models (Expand Search)
based field » pulsed field (Expand Search)
models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
field optimization » lead optimization (Expand Search), guided optimization (Expand Search), linear optimization (Expand Search)
library based » laboratory based (Expand Search)
binary mask » binary image (Expand Search)
mask models » risk models (Expand Search), base models (Expand Search), asr models (Expand Search)
based field » pulsed field (Expand Search)
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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. …”
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Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML
Published 2025“…To carry out our study, we have selected four such techniques(a) threshold optimization using (i) GHOST and (ii) the area under the precision–recall curve (AUPR) curve, (b) internal balancing method of AutoML and class-weight of machine learning methods, and (c) data balancing using SMOTETomekand generated 27 data sets considering nine different class ratios (i.e., the ratio of the positive class and total samples) from three data sets that belong to the drug discovery and development field. …”
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Portable Library for Homomorphic Encrypted Machine Learning on FPGA Accelerated Cloud Cyberinfrastructure
Published 2025“…This project will leverage our novel algorithmic, architectural, and memory optimizations on FPGAs to develop a portable library to enable secure and trustworthy ML inference. …”
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Portable Library for Homomorphic Encrypted Machine Learning on FPGA Accelerated Cloud Cyberinfrastructure
Published 2024“…This project will leverage our novel algorithmic, architectural, and memory optimizations on FPGAs to develop a portable library to enable secure and trustworthy ML inference. …”
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Diversity and specificity of lipid patterns in basal soil food web resources
Published 2019“…In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. …”
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<b>Portable Library for Homomorphic Encrypted Machine Learning on FPGA Accelerated Cloud Cyberinfrastructure</b>
Published 2023“…This project will leverage our novel algorithmic, architectural, and memory optimizations on FPGAs to develop a portable library to enable secure and trustworthy ML inference. …”
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Flowchart scheme of the ML-based model.
Published 2024“…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …”
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Presentation_1_Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction.pdf
Published 2023“…Based on the physical characteristics of summer sea ice, different algorithms are employed to optimize the prediction model. …”
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Presentation_1_Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction.pdf
Published 2023“…Based on the physical characteristics of summer sea ice, different algorithms are employed to optimize the prediction model. …”