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In Microsoft Windows applications programming, OLE Automation (later renamed to simply Automation [1] [2]) is an inter-process communication mechanism created by Microsoft.It is based on a subset of Component Object Model (COM) that was intended for use by scripting languages – originally Visual Basic – but now is used by several languages on Windows.
New features were OLE automation, drag-and-drop, in-place activation and structured storage. Monikers evolved from OLE 1 object names, and provided a hierarchical object and resource naming system similar to URLs or URIs, which were independently invented. Windows now has merged the two technologies supporting a URL Moniker type, and a Moniker ...
The OPC specification was based on the OLE, COM, and DCOM technologies developed by Microsoft Corporation for the Microsoft Windows operating system family. The specification defined a standard set of objects, interfaces e.g. IDL and methods for use in process control and manufacturing automation applications to facilitate interoperability.
Object Linking and Embedding (OLE), Microsoft's first object-based framework, was built on DDE and designed specifically for compound documents. It was introduced with Word and Excel in 1991, and was later included with Windows, starting with version 3.1 in 1992. An example of a compound document is a spreadsheet embedded in a Word document. As ...
It also includes Object Linking and Embedding/ActiveX (OLE) support allowing to interact with Windows programs via the OLEObject. [59] OLE Automation is an inter-process communication mechanism developed by Microsoft that is based on a subset of the Component Object Model (COM). This mechanism enables, among other things, the invocation of ...
SHSCRAP.DLL is part of the Object Linking and Embedding (OLE) mechanism. It implements support for shell scrap files, which are automatically created when you drag selected content from an OLE-capable application into an Explorer window or desktop, [13] but you can also use the Object Packager to create them. They can then be dragged into ...
Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. It is the combination of automation and ML. [1] AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment.
Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...