RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …”

Image processing workflow. by Denis Tamiev (7404980)

“…<p>Raw fluorescent microscope images (a) were processed with a binary segmentation algorithm, and clusters of bacterial cells were manually annotated. …”

Visualization of the image segmentation and labeling pipeline for the first frame of an example movie. by Miriam Schnitzerlein (21446136)

The steps of proposed method of RWMA detection using echocardiography images for RWMA detection, consisting with cardiac structure segmentation using a trained U-Net on both A4C an... by Sazzli Kasim (11218558)

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

3D Microvascular Image Data and Labels for Machine Learning by Natalie Holroyd (7099391)

“…The dataset contains images from a variety of imaging modalities, at different resolutions, using difference sources of contrast and featuring different organs/ pathologies. This data was use to train, test and validated a foundational model for 3D vessel segmentation, tUbeNet, which can be found on <a href="https://github.com/natalie11/tUbeNet" rel="noreferrer" target="_blank">github</a>. …”

Adaptive Inference for Change Points in High-Dimensional Data by Yangfan Zhang (6451946)

“…On the estimation front, we obtain the convergence rate of the maximizer of our test statistic standardized by sample size when there is one change-point in mean and <i>q</i> = 2, and propose to combine our tests with a wild binary segmentation algorithm to estimate the change-point number and locations when there are multiple change-points. …”

Key steps in neurodegeneration detection algorithm. by Andrew S. Clark (16510496)

Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model by Getachew S. Molla (6416744)

“…., nonelectrolyte, electrolyte, and solvate) in single and mixed solvents using a symmetrically reformulated electrolyte nonrandom two-liquid segment activity coefficient (eNRTL-SAC) model. The methodology incorporates key features of the symmetric eNRTL-SAC model structure to reduce the number of parameters and uses a hybrid of global search algorithms for parameter estimation. …”

Validation of image processing steps and metric results using images of a microfluidic device. by Gavrielle R. Untracht (11820311)

Flow chart of the algorithm. by Mukesh Karunanethy (18422857)

“…<p>Flow chart showing the algorithm pipeline, including time series normalization, filtering, feature extraction, feature reduction, and data splitting into training and testing. …”

Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports by Olivier Q. Groot (9370461)

“…The aim of this study was to develop a natural language processing (NLP) algorithm for binary classification (single metastasis versus two or more metastases) in bone scintigraphy reports of patients undergoing surgery for bone metastases.…”

DataSheet_1_Accurate Tumor Delineation vs. Rough Volume of Interest Analysis for 18F-FDG PET/CT Radiomics-Based Prognostic Modeling inNon-Small Cell Lung Cancer.docx by Shima Sepehri (11574997)

Fig 1 - by Monjoy Saha (12239792)

<b>Multimodal MRI radiomics</b><b> based on </b><b>habitat subregions of the tumor microenvironment</b><b> for predicting risk stratification in glioblastoma</b> by Han Wang (21457334)

“…</p><p dir="ltr">A fully automated approach involving label fusion from multiple deep learning algorithms was used to segment distinct tumor subregions histologically. …”

Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx by Yupeng Li (507508)

“…In bSRWPSO-FKNN, the core of which is to optimize the classification performance of FKNN through binary SRWPSO.…”

Fig 12 - by Nisha Yadav (366131)

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)

Experimental setup and trajectory estimation methodology. by Nouman Javed (16624785)