This report examines a Python-based credit card fraud detection model using logistic regression. The dataset contains transactions labeled as either fraudulent or non-fraudulent, and the analysis aims ...

This project aims to detect student depression by training a Decision Tree model using Python and NumPy, leveraging a well-prepared dataset from Kaggle. It includes detailed preprocessing, feature ...

Now, a team at HZB has developed an elegant method using a photo voltage to detect ... leading to a complex experimental set-up for the detection. Published in Nature Communications, a team ...

With the integration of multiple designs, various clock domains are introduced. In this paper, we present a solution for finding clock domain crossing glitch using a combination of formal verification ...

See how firms from Goldman Sachs to Bridgewater are using it. Welcome to Wall Street's AI era. Banks, hedge funds, asset managers, and private equity firms have been eager to use generative AI to ...

Machine learning plays a critical role in fraud detection by identifying patterns and anomalies in real-time. It analyzes large datasets to spot normal behavior ... of three unsupervised learning ...

This paper proposes a novel train surface defect detection model (ViLG) via visual-language knowledge guidance. By leveraging broad semantic knowledge of CLIP, the model compensates for the ...