Search alternatives:
composition optimization » composition estimation (Expand Search), operation optimization (Expand Search), composition identification (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
based composition » based decomposition (Expand Search), acid composition (Expand Search), based composite (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
composition optimization » composition estimation (Expand Search), operation optimization (Expand Search), composition identification (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
based composition » based decomposition (Expand Search), acid composition (Expand Search), based composite (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
-
1
-
2
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. …”
-
3
-
4
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. …”
-
5
Accelerated Design of Catalytic Water-Cleaning Nanomotors via Machine Learning
Published 2019“…However, the vast variety of nanoparticle designs prevents rapid identification of the optimal composition for a given application. In this study, we applied machine learning methods to predict the self-propulsion speed and water-cleaning efficiency of micro/nanomotors (MNMs), where the quality of machine learning predictions was evaluated based on the statistical values. …”