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surface optimization » surface contamination (Expand Search), resource optimization (Expand Search), swarm optimization (Expand Search)
scale optimization » whale optimization (Expand Search), swarm optimization (Expand Search), phase optimization (Expand Search)
data surface » earth surface (Expand Search), metal surface (Expand Search), total surface (Expand Search)
binary each » binary health (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
each scale » each stage (Expand Search)
surface optimization » surface contamination (Expand Search), resource optimization (Expand Search), swarm optimization (Expand Search)
scale optimization » whale optimization (Expand Search), swarm optimization (Expand Search), phase optimization (Expand Search)
data surface » earth surface (Expand Search), metal surface (Expand Search), total surface (Expand Search)
binary each » binary health (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
each scale » each stage (Expand Search)
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …”
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Steps in the extraction of 14 coordinates from the CT slices for the curved MPR.
Published 2025“…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). Along this optimized curve, 12 evenly spaced coordinates are extracted, and the curve is extended with an additional coordinate at each end, represented by the blue points in g).…”
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Flow diagram of the automatic animal detection and background reconstruction.
Published 2020“…If the identical blob that was detected in panel J (bottom) is found in any of the new subtracted binary images (cyan arrow), the animal is considered as having left its original position, and the algorithm continues. …”
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”