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A graphical abstract (or visual abstract [1]) is a graphical or visual equivalent of a written abstract. [2] [3] Graphical abstracts are a single image and are designed to help the reader to quickly gain an overview on a scholarly paper, research article, thesis or review: and to quickly ascertain the purpose and results of a given research, as well as the salient details of authors and journal.
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.
Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI . As with other text-to-image models, Flux generates images from natural language descriptions, called prompts .
The Stable Diffusion model supports the ability to generate new images from scratch through the use of a text prompt describing elements to be included or omitted from the output. [8] Existing images can be re-drawn by the model to incorporate new elements described by a text prompt (a process known as "guided image synthesis" [ 49 ] ) through ...
Supports a range of annotation types. Annotations are stored separately from the unmodified PDF file, or (since version 0.15 with Poppler 0.20) can be saved in the document as standard PDF annotations. Evince: GNU GPL: Yes Yes Default PDF and file viewer for GNOME; replaces GPdf. Supports addition and removal (since v3.14), of basic text note ...
An image generated with DALL-E 2 based on the text prompt 1960's art of cow getting abducted by UFO in midwest. Artificial intelligence art is visual artwork created or enhanced through the use of artificial intelligence (AI) programs. Artists began to create artificial intelligence art in the mid to late 20th century when the discipline was ...
DALL-E, DALL-E 2, and DALL-E 3 (stylised DALL·E, and pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.