The confidence curve of a binary image. by Dingming Yang (8505990)

The confidence change of the binary image after iteration. by Dingming Yang (8505990)

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

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. …”

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. …”

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

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. …”

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

Image1_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.JPEG by Wisnu Ananta Kusuma (9276182)

Image2_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.JPEG by Wisnu Ananta Kusuma (9276182)

Image4_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.jpg by Wisnu Ananta Kusuma (9276182)

Image5_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.jpg by Wisnu Ananta Kusuma (9276182)

Image3_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.JPEG by Wisnu Ananta Kusuma (9276182)

Overview of the segmentation algorithm. by Michael C. Robitaille (11949174)

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. …”

Binary leaf image rotated anti-clock wise from the origin degree to 40^<i>o</i>, 80^<i>o</i>, 120^<i>o</i>, and 160^<i>o</i> from left to ri... by Ali Ahmed (2567584)

Table4_Optimizing multi-environment trials in the Southern US Rice belt via smart-climate-soil prediction-based models and economic importance.xlsx by Melina Prado (19931685)

“…To address this challenge, we used soil information and ten years of historical weather data from the USA rice belt, which was translated into rice response based on the rice cardinal temperatures and crop stages. …”

Table3_Optimizing multi-environment trials in the Southern US Rice belt via smart-climate-soil prediction-based models and economic importance.xlsx by Melina Prado (19931685)

“…To address this challenge, we used soil information and ten years of historical weather data from the USA rice belt, which was translated into rice response based on the rice cardinal temperatures and crop stages. …”

Image2_Optimizing multi-environment trials in the Southern US Rice belt via smart-climate-soil prediction-based models and economic importance.jpeg by Melina Prado (19931685)

“…To address this challenge, we used soil information and ten years of historical weather data from the USA rice belt, which was translated into rice response based on the rice cardinal temperatures and crop stages. …”