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2. Ideogram (text-to-image model) - Wikipedia

   en.wikipedia.org/wiki/Ideogram_(text-to-image_model)

   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]

3. Flux (text-to-image model) - Wikipedia

   en.wikipedia.org/wiki/Flux_(text-to-image_model)

   The tools consisting of Flux.1 Fill for inpainting and outpainting, Flux.1 Depth for control based on extracted depth map of input images and prompts, Flux.1 Canny for control based on extracted canny edges of input images and prompts, and Flux.1 Redux for mixing existing input images and prompts. Each tools are available in both Dev and Pro ...

4. List of concept- and mind-mapping software - Wikipedia

   en.wikipedia.org/wiki/List_of_concept-_and_mind...

   Concept mapping and mind mapping software is used to create diagrams of relationships between concepts, ideas, or other pieces of information. It has been suggested that the mind mapping technique can improve learning and study efficiency up to 15% over conventional note-taking. [1]

5. AI Image Generators Will Blow Your Mind. Here Are the 3 Best ...

   www.aol.com/lifestyle/ai-image-generators-blow...

   My comparison analyzed cost, ease of use, image resolution, dynamic range, composition, creativity, post-processing, and even speed. Along with those factors I also fed each with identical prompts ...

6. Text-to-image model - Wikipedia

   en.wikipedia.org/wiki/Text-to-image_model

   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.

7. Text-to-image personalization - Wikipedia

   en.wikipedia.org/wiki/Text-to-image_personalization

   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.