Discover how AI is revolutionizing veterinary radiology, and learn how algorithms support specialists for faster, more ...
Abstract: This innovative practice full paper describes how to integrate generative Artificial Intelligence (AI) with Data Structures and Algorithm Analysis (CS2) homework at Oklahoma State University ...
As AI becomes more common and decisions more data-driven, a new(ish) form of information is on the rise: synthetic data. And some proponents say it promises more privacy and other vital benefits. Data ...
A deal to prevent a US TikTok ban is now in place. The app’s algorithm will be copied, overseen by Oracle, and retrained using only American user data. This new, separate system addresses national ...
Precision crack analysis in concrete structures using CNN, SVM, and KNN: a machine learning approach
Cracks in structures are discontinuities that occur due to stress, material degradation, or design flaws, compromising structural integrity. Detecting and analyzing cracks is crucial for assessing ...
Welcome to the Data Structures and Algorithms Repository! My aim for this project is to serve as a comprehensive collection of problems and solutions implemented in Python, aimed at mastering ...
Abstract: To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes ...
1 The College of Computer, Qinghai Normal University, Xining, China 2 Department of Mechanical and Electrical Engineering, College of Xining Urban Vocational and Technical, Xining, China Traditional ...
Sparse canonical correlation analysis (sCCA) has been a useful approach for integrating different high-dimensional datasets by finding a subset of correlated features that explain the most correlation ...
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