Proposed Algorithm. by Hend Bayoumi (22693738)

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…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. …”

Comparisons between ADAM and NADAM optimizers. by Hend Bayoumi (22693738)

An Example of a WPT-MEC Network. by Hend Bayoumi (22693738)

Related Work Summary. by Hend Bayoumi (22693738)

Simulation parameters. by Hend Bayoumi (22693738)

Training losses for N = 10. by Hend Bayoumi (22693738)

Normalized computation rate for N = 10. by Hend Bayoumi (22693738)

Summary of Notations Used in this paper. by Hend Bayoumi (22693738)

datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf by Jan Tönshoff (10192709)

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

“…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. …”

Supplementary Material 8 by Nishitha R Kumar (19750617)

“…</p><p dir="ltr">When applied to AMR prediction, SMOTE enhances the ability of classification models to accurately identify resistant <i>Escherichia coli</i> strains by balancing the dataset, ensuring that machine learning algorithms do not overlook rare resistance patterns. …”