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Image2Text technology was created by Cortica, an Israel-based startup whose technology simulates the performance of the human cortex so that computers recognize images with a high degree of accuracy. [1] Image2Text is the result of 10 years in research and development and is protected by more than 50 patents. [2]
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.
A very simple Copy & Paste Excel-to-Wiki Converter; A free open source tool to convert from CSV and Excel files to wiki table format: csv2other; Spreadsheet-to-MediaWiki-table-Converter This class constructs a MediaWiki-format table from an Excel/GoogleDoc copy & paste. It provides a variety of methods to modify the style.
Many image formats are native to one specific graphics application and are not offered as an export option in other software, due to proprietary considerations. An example of this is Adobe Photoshop 's native PSD-format (Prevention of Significant Deterioration), which cannot be opened in less sophisticated programs for image viewing or editing ...
A Wikipedia reader can click on the thumbnail, or on the small double-rectangle icon below it, to see the corresponding file page which will let the user see the image in its original size. Although the above text may appear in multiple lines for formatting purposes, the actual image text is on one line, as it uses spaces without any line breaks.
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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.
An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
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