Search alternatives:
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
laboratory tests » laboratory data (Expand Search)
web optimization » b optimization (Expand Search), yet optimization (Expand Search), led optimization (Expand Search)
tests web » tests were (Expand Search), tests when (Expand Search), tests per (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
laboratory tests » laboratory data (Expand Search)
web optimization » b optimization (Expand Search), yet optimization (Expand Search), led optimization (Expand Search)
tests web » tests were (Expand Search), tests when (Expand Search), tests per (Expand Search)
-
1
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. …”
-
2
CorrEA: A Web Server for Optimizing Correlations between Calculated Energies and Activities in Ligand–Receptor Systems Considering Multiple Binding Site Conformations
Published 2025“…With this in mind, in this work, we present the novel web server CorrEA with a simple and innovative way of considering the flexibility of ligand–protein systems. …”
-
3
Diversity and specificity of lipid patterns in basal soil food web resources
Published 2019“…In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. …”
-
4
-
5
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. …”