Search alternatives:
based optimization » whale optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
binary sample » final sample (Expand Search), binary people (Expand Search), intra sample (Expand Search)
binary state » binary image (Expand Search), binary data (Expand Search)
sample based » samples based (Expand Search), scale based (Expand Search)
based optimization » whale optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
binary sample » final sample (Expand Search), binary people (Expand Search), intra sample (Expand Search)
binary state » binary image (Expand Search), binary data (Expand Search)
sample based » samples based (Expand Search), scale based (Expand Search)
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 2025“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”
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ROC curve for binary classification.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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Confusion matrix for binary classification.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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The flowchart of the proposed algorithm.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity
Published 2019“…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. …”
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Summary of literature review.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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Topic description.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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Notations along with their descriptions.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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Detail of the topics extracted from DUC2002.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level
Published 2021“…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”
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Testing results for classifying AD, MCI and NC.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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Summary of existing CNN models.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”