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

SHAP bar plot. حسب Meng Cao (105914)

SHAP summary plot. حسب Meng Cao (105914)

A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some high-dimensional datasets usi... حسب Olaide N. Oyelade (14047002)

A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some medium-sized dimensional data... حسب Olaide N. Oyelade (14047002)

A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some small-sized dimensional datas... حسب Olaide N. Oyelade (14047002)

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm حسب 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. …"

Fig 4 - حسب Olaide N. Oyelade (14047002)

Fig 7 - حسب Olaide N. Oyelade (14047002)

Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf حسب Sai Sakunthala Guddanti (17739363)

"…A support vector machine (SVM) is attractive because binary classification can be represented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization (QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing—classical, quantum, and hybrid—an attractive approach to explore. …"

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

Sample image for illustration. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. Finally, the plot of location feature distance illustrates that CBFD exhibits minimal distance compared to DITF and Histogram of Oriented Gradients (HOG). …"

Comparison analysis of computation time. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. Finally, the plot of location feature distance illustrates that CBFD exhibits minimal distance compared to DITF and Histogram of Oriented Gradients (HOG). …"

Process flow diagram of CBFD. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. Finally, the plot of location feature distance illustrates that CBFD exhibits minimal distance compared to DITF and Histogram of Oriented Gradients (HOG). …"

Precision recall curve. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. Finally, the plot of location feature distance illustrates that CBFD exhibits minimal distance compared to DITF and Histogram of Oriented Gradients (HOG). …"

Quadratic polynomial in 2D image plane. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. Finally, the plot of location feature distance illustrates that CBFD exhibits minimal distance compared to DITF and Histogram of Oriented Gradients (HOG). …"

DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx حسب Massaine Bandeira e Sousa (7866242)

"…Fifteen roots from five plants per plot, featuring diameters ranging from 4 to 7 cm, were randomly chosen for cooking analysis and spectral data collection. …"

Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx حسب Massaine Bandeira e Sousa (7866242)

"…Fifteen roots from five plants per plot, featuring diameters ranging from 4 to 7 cm, were randomly chosen for cooking analysis and spectral data collection. …"

Flow diagram of the automatic animal detection and background reconstruction. حسب David Tadres (9120564)

"…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …"