Abstract: The accurate land cover mapping of the Earth's surface using Earth observation data is one of the most studied, but yet the most challenging tasks of remote sensing field, particularly when ...

Abstract: In complex industrial manufacturing processes, various defects may occur in products because of the poor quality of the equipment, materials, and human factors. These defects may lead to ...

This project is targeting people who want to learn internals of ml algorithms or implement them from scratch. The code is much easier to follow than the optimized libraries and easier to play with.

Comparative Analysis of Data Mining algorithms (KNN, Naive Bayes, SVM) for Diabetes prediction. Features an 88% accuracy SVM model deployed as a Clinical Decision Support System. - Muhamad-Shahan/D ...

Six ML algorithms (Extreme Gradient Boosting [XGBoost], logistic regression (LR), Light Gradient Boosting Machine [LightGBM], random forest [RF], support vector machine [SVM], and k-nearest neighbor ...

What about ChatGPT and related large AI Systems? How will they impact us all? As a longtime researcher in AI, I'm excited about the ways in which these new AI systems can improve our healthcare, ...

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

Background The prompt and precise diagnosis of active pulmonary tuberculosis (TB) is crucial for controlling this disease and ...

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Multiple ML models—including logistic regression, random forest (RF), extreme gradient boosting (XGBoost), support vector machine, neural network, LightGBM, and CatBoost—were developed using 10-fold ...