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. …”

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

Classification standard of highway tunnels. by Chunquan Dai (16819414)

Classification thresholds for assessment of technical status of civil structures. by Chunquan Dai (16819414)

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. …”

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

<b>BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification</b> by BRISC Dataset (22559540)

“…<p dir="ltr"><b>BRISC 2025 — Brain Tumor MRI Dataset</b></p><p dir="ltr">BRISC (BRain tumor Image Segmentation & Classification) — a curated, expert-annotated T1 MRI dataset for multi-class brain tumor classification and pixel-wise segmentation.…”

Calibration curves for NLP classification. by Charlene Jennifer Ong (8997278)

Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx by Veera Narayana Balabathina (22518524)

“…</p>Methods<p>Thirteen supervised classification algorithms were comparatively evaluated, encompassing traditional spectral/statistical classifiers—Maximum Likelihood, Mahalanobis Distance, Minimum Distance, Parallelepiped, Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Binary Encoding—and machine learning algorithms including Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). …”

UNet++ type architecture [68] used for all the problems in this paper. by Dylan D. Ray (3741823)

DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx by Jun Zhang (48506)

“…Purpose<p>To develop and validate a deep learning radiomics (DLR) model that uses X-ray images to predict the classification of osteoporotic vertebral fractures (OVFs).…”

Recognition of each neuron’s digital identity. by Yuxiang Wu (748543)

Image_1_A predictive model based on random forest for shoulder-hand syndrome.JPEG by Suli Yu (14947807)

Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay by Younseong Song (9967421)

“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”

Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay by Younseong Song (9967421)

“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”

Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay by Younseong Song (9967421)

“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”

Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay by Younseong Song (9967421)

“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”

Deactivated Cas9-Engineered Magnetic Micromotors toward a Point-of-Care Digital Viral RNA Assay by Younseong Song (9967421)

“…A convolutional neural network classification-based multiobject tracking algorithm, CNN-MOT, accurately measures the change in micromotor motion, facilitating the binary digital assay format (“1” or “0”) for simplified result interpretation without user bias. …”