The Data Quality Maturity Model can help guide organizations on their data quality journey. It provides a framework for companies to understand where they are, where they’ve been, and where they still ...

Abstract: In this article, we have demonstrated a novel, generalized Seq2Dense U-Net model for classifying different activities (time-series data obtained from an accelerometer and gyroscope) and ...

Washington-based Starcloud launched a satellite with an Nvidia H100 graphics processing unit in early November, sending a chip into outer space that's 100 times more powerful than any GPU compute that ...

The segmentation of gastrointestinal (GI) organs, including the stomach, small intestine, and large intestine, is crucial for radio oncologists to plan effective cancer therapy. This study presents an ...

Data modeling and data analysis are two fundamental ideas in the contemporary field of data science that frequently overlap but are very different from one another. Although both are crucial in ...

Machine learning, particularly the training of large foundation models, relies heavily on the diversity and quality of data. These models, pre-trained on vast datasets, are the foundation of many ...

Generative AI’s reliance on extensive data has led to the use of synthetic data, which Rice University research shows can cause a feedback loop that degrades model quality over time. This process, ...

This repository contains Group 7 - QuickEV's AoL (Assurance of Learning) Final Project for COMP6100001 - Software Engineering and COMP6884001 - Agile Software Development courses.