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Computer Vision Annotation Tool (CVAT) is a free, open source, web-based image and video annotation tool used for labeling data for computer vision algorithms. Originally developed by Intel , CVAT is designed for use by a professional data annotation team, with a user interface optimized for computer vision annotation tasks.
Manual image annotation is the process of manually defining regions in an image and creating a textual description of those regions. Such annotations can for instance be used to train machine learning algorithms for computer vision applications. This is a list of computer software which can be used for manual annotation of images.
Output of DenseCap "dense captioning" software, analysing a photograph of a man riding an elephant. Automatic image annotation (also known as automatic image tagging or linguistic indexing) is the process by which a computer system automatically assigns metadata in the form of captioning or keywords to a digital image.
Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.
Captions is a video-editing and AI research company headquartered in New York City. Their flagship app, Captions , is available on iOS , Android , and Web and offers a suite of tools aimed at streamlining the creation and editing of videos.
In February 2023, Otter.ai launched an AI meeting assistant called OtterPilot, available to all users, which automates meetings, with an AI-generated summary of key meeting topics, automated capture of images of slides shared during virtual meetings, and real-time meeting notes that can be shared and collaborated on.
Microsoft invested $1.5 billion in G42 earlier this year, giving the U.S. company a minority stake and a board seat. As part of the deal, G42 would use Microsoft's cloud services to run its AI ...
Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos. [ 6 ] OpenAI trained the model using publicly available videos as well as copyrighted videos licensed for the purpose, but did not reveal the number or the exact source of the videos. [ 4 ]
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