ABSTRACT: This study proposes a multimodal AI model for classifying Vietnamese digital learning materials by integrating three key information sources: text content, image and graphic features, and ...
A metadata-driven framework for orchestrating Databricks Lakeflow Jobs. Package as a library and run as a single task in a Lakeflow Jobs to continuously monitor for metadata changes and automatically ...
FedM2CT consists of 3 modules, i.e., task-specific iRadonMAP (TS-iRadonMAP), condition-prompted mutual learning (CPML), and federated metadata learning (FMDL). TS-iRadonMAP performs the local CT image ...
At a time when adult education is being digitized at breakneck speed, a counter-trend is asserting itself: that of a return to the body, to materiality and to objects as living supports for learning.
Who needs rewrites? This metadata-powered architecture fuses AI and ETL so smoothly, it turns pipelines into self-evolving engines of insight. In the fast-evolving landscape of enterprise data ...
Introduction: Recent advances in artificial intelligence have transformed the way we analyze complex environmental data. However, high-dimensionality, spatiotemporal variability, and heterogeneous ...
As virtual reality technology continues to develop, more colleges and universities are integrating it into the student experience inside and outside of the classroom. A recent survey of chief ...
What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.
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