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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.
Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.
Generative AI systems such as MusicLM [72] and MusicGen [73] can also be trained on the audio waveforms of recorded music along with text annotations, in order to generate new musical samples based on text descriptions such as a calming violin melody backed by a distorted guitar riff.
A tree can be defined by 3-D graphical types as type TREE = figure (var BRANCHES: TEXT; NBRANCHES: INTEGER; POSITION: VECTOR; HEIGHT, LENGTH:REAL); where BRANCHES is a file of kinds of branches, NBRANCHES is the number of branches, POSITION is the position of the trunk, HEIGHT is the height of the trunk, and LENGTH is the length of the branches.
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 ...
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.
Information visualization, on the other hand, deals with multiple, large-scale and complicated datasets which contain quantitative (numerical) data as well as qualitative (non-numerical, i.e. verbal or graphical) and primarily abstract information and its goal is to add value to raw data, improve the viewers' comprehension, reinforce their ...