The illustration depicts our CQ-CNN architecture for binary image classification. حسب Mominul Islam (3513758)

Initial parameter settings for the optimization algorithms. حسب Doaa Sami Khafaga (21463870)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. حسب Tehnan I. A. Mohamed (16846175)

Line plots showing performance trends for six evaluation metrics across CNN combined with different bio-inspired optimization algorithms. حسب Doaa Sami Khafaga (21463870)

Bar chart comparing the average fitness values of various feature selection algorithms. حسب Doaa Sami Khafaga (21463870)

Box plots with swarm overlays for six feature selection algorithms, annotated with mean and standard deviation values. حسب Doaa Sami Khafaga (21463870)

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment حسب Jianfang Cao (1881379)

"…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …"

Correlation heatmap of performance scores among different feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. حسب Doaa Sami Khafaga (21463870)

Density distribution plot of performance metrics for various feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. حسب Doaa Sami Khafaga (21463870)

Summary of existing CNN models. حسب Nicodemus Songose Awarayi (18414494)

Feature selection process. حسب Balraj Preet Kaur (20370832)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب Se-Hee Jo (20554623)

الموضوعات:

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. حسب Benjamin Gallois (10131683)

Schematic of iteration process of IDE-IIGA. حسب Ling Zhao (111365)

Proposed Algorithm. حسب Hend Bayoumi (22693738)

"…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …"

Homomorphic binary tree. حسب Jianhua He (341366)

Classification baseline performance. حسب Doaa Sami Khafaga (21463870)

"…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. …"

Feature selection results. حسب Doaa Sami Khafaga (21463870)

"…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. …"