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)

Optimum solutions and tuning of the dependent variables for various cases based on the PSO technique (standard IEEE 30-bus test network). by Abdullah Khan (377292)

Schematic of the disrupted network considered in the case study. by Jiefei Zhang (8787494)

Schematic of the disrupted network considered in the case study. by Jiefei Zhang (8787494)

Optimum tuning of the dependent variables for various cases using the HFPSO technique (standard IEEE 30-bus test network). by Abdullah Khan (377292)

Bivariate analysis using line plot for casing, bearing & impeller vs pressure. by Gaurav Sandeep Dave (21519884)

Comparative discussion based on routing. by Shanthi Amgothu (17692146)

“…Here, RNBJSO is the combination of Namib Beetle Optimization (NBO), Remora Optimization Algorithm (ROA) and Jellyfish Search optimization (JSO). …”

Optimization parameters for the three treatment plans performed for the homogeneous and heterogeneous phantoms. by Masashi Yagi (3186909)

Subjects:

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

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

“…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”

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

“…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”

The <i>D</i>_<i>98</i> in the CTV and the for the nominal scenario optimized using the WC algorithm in homogeneous and heterogeneous phantom. by Masashi Yagi (3186909)

Subjects:

The <i>D</i>_<i>98</i> in the CTV and the for the nominal scenario optimized using the SC algorithm in homogeneous and heterogeneous phantoms. by Masashi Yagi (3186909)

Subjects:

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

“…Future work aims to generalize this algorithm for broader biological applications by training additional Cellpose models and adapting the A* framework.…”

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. …”

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)

The <i>D</i>_<i>98</i> in the CTV and the for the nominal scenario in the patient case. by Masashi Yagi (3186909)

Subjects:

Optimization traces for six datasets and four NMTF optimization methods. by Andrej Čopar (6824375)