Search alternatives:
segmentation algorithm » selection algorithm (Expand Search)
feature segmentation » feature representation (Expand Search), feature selection (Expand Search), image segmentation (Expand Search)
data feature » data figure (Expand Search), each feature (Expand Search), a feature (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
swarm » warm (Expand Search)
segmentation algorithm » selection algorithm (Expand Search)
feature segmentation » feature representation (Expand Search), feature selection (Expand Search), image segmentation (Expand Search)
data feature » data figure (Expand Search), each feature (Expand Search), a feature (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
swarm » warm (Expand Search)
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…<p dir="ltr">The first algorithm for segmentation and localization (see PathOlOgics_script_1; segment & localize using a pen) relied on manually tracing the borders of each cell using a digital pen tool on a big touchscreen display showing source images/patches. …”
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3D Microvascular Image Data and Labels for Machine Learning
Published 2024“…The dataset contains images from a variety of imaging modalities, at different resolutions, using difference sources of contrast and featuring different organs/ pathologies. This data was use to train, test and validated a foundational model for 3D vessel segmentation, tUbeNet, which can be found on <a href="https://github.com/natalie11/tUbeNet" rel="noreferrer" target="_blank">github</a>. …”
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Adaptive Inference for Change Points in High-Dimensional Data
Published 2021“…On the estimation front, we obtain the convergence rate of the maximizer of our test statistic standardized by sample size when there is one change-point in mean and <i>q</i> = 2, and propose to combine our tests with a wild binary segmentation algorithm to estimate the change-point number and locations when there are multiple change-points. …”
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Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model
Published 2019“…., nonelectrolyte, electrolyte, and solvate) in single and mixed solvents using a symmetrically reformulated electrolyte nonrandom two-liquid segment activity coefficient (eNRTL-SAC) model. The methodology incorporates key features of the symmetric eNRTL-SAC model structure to reduce the number of parameters and uses a hybrid of global search algorithms for parameter estimation. …”
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Flow chart of the algorithm.
Published 2024“…<p>Flow chart showing the algorithm pipeline, including time series normalization, filtering, feature extraction, feature reduction, and data splitting into training and testing. …”
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<b>Multimodal MRI radiomics</b><b> based on </b><b>habitat subregions of the tumor microenvironment</b><b> for predicting risk stratification in glioblastoma</b>
Published 2025“…</p><p dir="ltr">A fully automated approach involving label fusion from multiple deep learning algorithms was used to segment distinct tumor subregions histologically. …”
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Thesis-RAMIS-Figs_Slides
Published 2024“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”
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