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. …”

Urgent versus nonurgent binary classification performance. by Kyung Won Kwon (18150416)

Diagnostic performance for determining malignancy; binary classification. by Seung Seog Han (4782486)

An example of 2-dimensional non-linearly separable and non-separable data for binary classification. by Yuji Oyamada (11714754)

Performance of the proposed method for binary classification of lung cancer. by Md. Sabbir Hossain (9958939)

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Graphical comparison of binary class lung cancer classification with different approaches. by Md. Sabbir Hossain (9958939)

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Random forest binary classification of the colorized Corona image for the RSK region, Morocco (1972). by Safia Loulad (16913691)

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

Effect of image resolution on the performance of the binary classifier algorithm in predicting occurrence of a bird target(s) on an individual image using the validation imagery se... by Tsung-Wei Ke (18297551)

Accuracy assessment of 2017 binary classification and multi-classification result (OA(Overall accuracy), PA(Producer accuracy), UA(User accuracy), ML(Maximum likelihood)). by Lei Liang (326409)

Applying the proposed image enhancement algorithm. by Nicodemus Songose Awarayi (18414494)

(a) Accuracy and (b) loss curves of training and validation during binary class classification for 512 features extracted by the CNN. by Md. Sabbir Hossain (9958939)

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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. …”

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. …”

Receiver Operating Characteristic (ROC) curves for classification of vessels pixels on the DRIVE and STARE databases. by Hesham Abdushkour (16617908)

Effect of training regions on the performance of the Mask R-CNN detection algorithm based on the refined annotation bounding boxes. by Tsung-Wei Ke (18297551)

ROC curves of the proposed method for binary class classification: (A) GNB, (B) GBM, (C) KNN, (D) SVM, (E) RF, and (F) Ensemble learning. by Md. Sabbir Hossain (9958939)

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Performance of the baseline SVM and Mask R-CNN detection algorithms based on the original, manually-derived annotated bounding boxes. by Tsung-Wei Ke (18297551)

Effect of image resolution on the performance of the Mask R-CNN algorithm in detecting individual bird instances as applied to the validation imagery set. by Tsung-Wei Ke (18297551)