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The image transfer medium was originally a stencil made from waxed mulberry paper. Later this became an immersion-coated long-fiber paper, with the coating being a plasticized nitrocellulose . This flexible waxed or coated sheet is backed by a sheet of stiff card stock, with the two sheets bound at the top.
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.
Ideogram is a freemium text-to-image model developed by Ideogram, Inc. using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The model is capable of generating legible text in the images compared to other text-to-image models. [1] [2]
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.
During the 1980s, a convergence began in some high-end machines towards what came to be called a multi-function printer: a device that combined the roles of a photocopier, a fax machine, a scanner, and a computer network-connected printer. Low-end machines that can copy and print in color have increasingly dominated the home-office market as ...
A heliographic copier or heliographic duplicator [1] is an apparatus used in the world of reprography for making contact prints on paper from original drawings made with that purpose on tracing paper, parchment paper or any other transparent or translucent material using different procedures.
Laser printing is an electrostatic digital printing process. It produces high-quality text and graphics (and moderate-quality photographs) by repeatedly passing a laser beam back and forth over a negatively charged cylinder called a "drum" to define a differentially charged image. [1]
Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models. In this task, a generative model that was trained on large-scale data (usually a foundation model ), is adapted such that it can generate images of novel, user-provided concepts.
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