Search alternatives:
weight optimization » design optimization (Expand Search), joint optimization (Expand Search)
from optimization » fox optimization (Expand Search), swarm optimization (Expand Search), codon optimization (Expand Search)
image weight » tag weight (Expand Search), more weight (Expand Search)
scale from » scale free (Expand Search), scale flow (Expand Search)
weight optimization » design optimization (Expand Search), joint optimization (Expand Search)
from optimization » fox optimization (Expand Search), swarm optimization (Expand Search), codon optimization (Expand Search)
image weight » tag weight (Expand Search), more weight (Expand Search)
scale from » scale free (Expand Search), scale flow (Expand Search)
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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
Published 2019“…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …”
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Datasets and their properties.
Published 2023“…To address this, we proposed a novel hybrid binary optimization capable of effectively selecting features from increasingly high-dimensional datasets. …”
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Parameter settings.
Published 2023“…To address this, we proposed a novel hybrid binary optimization capable of effectively selecting features from increasingly high-dimensional datasets. …”
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Image processing workflow.
Published 2020“…<p>Raw fluorescent microscope images (a) were processed with a binary segmentation algorithm, and clusters of bacterial cells were manually annotated. …”
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Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf
Published 2019“…The Digital Annealer's algorithm is currently based on simulated annealing; however, it differs from it in its utilization of an efficient parallel-trial scheme and a dynamic escape mechanism. …”
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DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx
Published 2021“…A total of 4,198 radiomics features were extracted from the pre-biopsy multi-parametric MRI (including dynamic contrast-enhancement T1-weighted images, fat-suppressed T2-weighted images, and apparent diffusion coefficient map) of each patient. …”
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Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
Published 2025“…Both the SVM model with a linear kernel and the one with an RBF kernel achieved identical results. Optimization with GridSearchCV corroborated this stagnation, identifying a simple linear model (C=0.05, gamma='scale') as the optimal configuration, indicating that the additional complexity of nonlinear kernels did not confer predictive gains. …”
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Flow diagram of the automatic animal detection and background reconstruction.
Published 2020“…(C) The current image (in this example, the second image of the experiment) is then subtracted from the mean image shown in panel B. (D) The histogram of the subtracted image shows most gray scale values to be 0. …”