ROC curve for binary classification. by Nicodemus Songose Awarayi (18414494)

“…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”

Confusion matrix for binary classification. by Nicodemus Songose Awarayi (18414494)

“…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”

A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

“…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. The A* algorithm then evaluated connectivity by minimizing Euclidean distance and heuristic cost between cells. …”

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

Dataset 2: Zip file containing the Tables of the presented method and results by Suchismita Behera (22027316)

Algorithm flow of the GA-BPNN model. by Xiying Wang (4859998)

“…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …”

Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files by Suchismita Behera (22027316)

“…<p dir="ltr">Figures represented here illustrates the <b>metaheuristic-based band selection framework</b> for hyperspectral image classification using <b>Binary Jaya Algorithm enhanced with a mutation operator</b> to improve population diversity and avoid premature convergence. …”

A new fast filtering algorithm for a 3D point cloud based on RGB-D information by Chaochuan Jia (7256237)

“…Then, the optimal segmentation threshold of the V image that is calculated by using the Otsu algorithm is applied to segment the color mapping image into a binary image, which is used to extract the valid point cloud from the original point cloud with outliers. …”

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

“…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …”

Parameter settings. by Qingbo Tu (22641033)

“…Compared with a single machine learning or heuristic algorithm, this model significantly reduces the unit prediction error under load fluctuations and extreme weather scenarios. …”

Indicator settings. by Qingbo Tu (22641033)

“…Compared with a single machine learning or heuristic algorithm, this model significantly reduces the unit prediction error under load fluctuations and extreme weather scenarios. …”

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

The 147th single trace. by Zhenjing Yao (22189970)

Testing results for classifying AD, MCI and NC. by Nicodemus Songose Awarayi (18414494)

“…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”

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

“…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”

Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

“…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …”

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

Example of sample data. by Xiying Wang (4859998)

“…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …”

Structure of BPNN. by Xiying Wang (4859998)

“…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …”

The workflow of EGA-BPNN. by Xiying Wang (4859998)

“…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …”