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 ...
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 ...
The current Model Context Protocol (MCP) specification is inadequate to support the development of truly interoperable, intelligent, and user-friendly client applications due to a fundamental ...
This issue focuses on designing a comprehensive movie metadata schema that seamlessly integrates with our existing validation framework while supporting Constitutional AI requirements. The schema must ...
To acknowledge excellence in the design and implementation of online learning objects. The committee accepts submissions and searches for online learning objects that effectively support student ...
Abstract: This standard is a combination of new and existing metadata terms that were contextualized around learning and bundled with the purpose of addressing many of the common use cases of metadata ...
Unlock S3 data insights effortlessly with AWS' rich metadata capture; query objects by key, size, tags, and more using Athena, Redshift, and Spark at scale. Customers will benefit from capturing ...
Abstract: A conceptual data schema that defines the structure of a metadata instance for a learning object is specified in this standard. For this standard, a learning object is defined as any entity, ...
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