We first adopt a human-guided machine learning framework to develop a new dataset for hyperpartisan news title detection with 2,200 manually labeled and 1.8 million machine-labeled titles that were posted from 2014 to the present by nine representati...
The applied research is the design and development of an automated folding and sewing machine for pleated pants. It represents a significant advancement in addressing the challenges associated with manual sewing processes. Traditional methods for cre...
The development of Machine Learning (ML) models is more than just a special case of software development (SD): ML models acquire properties and fulfill requirements even without direct human interaction in a seemingly uncontrollable manner. Nonethele...
Full reference of LinkedIn answers 2024 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test ques…
In this bachelor thesis, we show how four different machine learning methods (Long Short-Term Memory, Random Forest, Support Vector Machine Regression, and k-Nearest Neighbor) perform compared to already successfully applied trading strategies such a...
Bearing fault diagnosis is important in condition monitoring of any rotating machine. Early fault detection in machinery can save millions of dollars in emergency maintenance cost. Different techniques are used for fault analysis such as short time Fourier tra…
A simple library for creating state machines in C# code (⭐ 6116)
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Imaging fluorescent disease biomarkers in tissues and skin is a non-invasive method to screen for health conditions. We report an automated process that combines intraoral fluorescent porphyrin biomarker imaging, clinical examinations and machine lea...
The convergence of fully homomorphic encryption (FHE) and machine learning offers unprecedented opportunities for private inference of sensitive data. FHE enables computation directly on encrypted data, safeguarding the entire machine learning pipeli...
Large language models trained on web-scale corpora can memorize undesirable data containing misinformation, copyrighted material, or private or sensitive information. Recently, several machine unlearning algorithms have been proposed to eliminate the...
A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x
A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x
The linguistic diversity across the African continent presents different challenges and opportunities for machine translation. This study explores the effects of data augmentation techniques in improving translation systems in low-resource African la...
Machine learning (ML) models have been quite successful in predicting outcomes in many applications. However, in some cases, domain experts might have a judgment about the expected outcome that might conflict with the prediction of ML models. One mai...