Robustness of the optimization process in a real dataset. by Neta Ravid Tannenbaum (2940351)

“…<p>S3 Fig shows the results of the optimization process for different start points supplied to the optimization function. …”

A method to concatenate multiple short time series for evaluating dynamic behaviour during walking by Stefan Orter (6786098)

“…The collected time series were cut into multiple shorter time series of varying lengths and subsequently concatenated using a novel algorithm that identifies similar poses in successive time series in order to determine an optimal concatenation time point. …”

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …”

Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx by Ali Nabavi (21097424)

“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…</li><li>The dataframe of extracted colour features from all leaf images and lab variables (ecophysiological predictors and variables to be predicted)</li><li>Set of scripts used for image pre-processing, features extraction, data analytsis, visualization and Machine learning algorithms training, using ImageJ, R and Python.…”