Search alternatives:
surface optimization » surface contamination (Expand Search), resource optimization (Expand Search), swarm optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
data surface » earth surface (Expand Search), metal surface (Expand Search), total surface (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
surface optimization » surface contamination (Expand Search), resource optimization (Expand Search), swarm optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
data surface » earth surface (Expand Search), metal surface (Expand Search), total surface (Expand Search)
binary data » primary data (Expand Search), dietary data (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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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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Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
Published 2024“…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”
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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.…”