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)

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. …”

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.…”

Network simulation of the proposed method. by Nanavath Kiran Singh Nayak (22184565)

Simulation parameters of SDN network. by Nanavath Kiran Singh Nayak (22184565)

Simulation parameters of DDcGAN. by Nanavath Kiran Singh Nayak (22184565)

Simulation results. by Zhen Wang (72451)

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)

Active sonar echo simulation. by Zhen Wang (72451)

BenchmarkDataNLP.jl.zip by Alexander V. Mantzaris (21376517)

Summary of existing CNN models. 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. …”

Research in the Field of Medical Informatics at the ZMI, Dresden, Germany - JOIN US by Markus Wolfien (3203601)

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by D. Andrew Brown (6584837)

Reinforcement Learning for Autonomous Process Control in Industry 4.0: Advantages and Challenges by Nuria Nievas (19331156)

“…<p>In recent years, the integration of intelligent industrial process monitoring, quality prediction, and predictive maintenance solutions has garnered significant attention, driven by rapid advancements in digitalization, data analytics, and machine learning. …”

Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf by 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. …”