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2. Optical character recognition - Wikipedia

   en.wikipedia.org/wiki/Optical_character_recognition

   Video of the process of scanning and real-time optical character recognition (OCR) with a portable scanner. Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo (for example the text on signs and ...

3. Text-to-image model - Wikipedia

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

   A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom, as a result of advances in deep neural networks. In 2022, the output of state-of-the-art text-to ...

4. Stable Diffusion - Wikipedia

   en.wikipedia.org/wiki/Stable_Diffusion

   Diagram of the latent diffusion architecture used by Stable Diffusion The denoising process used by Stable Diffusion. The model generates images by iteratively denoising random noise until a configured number of steps have been reached, guided by the CLIP text encoder pretrained on concepts along with the attention mechanism, resulting in the desired image depicting a representation of the ...

5. DALL-E - Wikipedia

   en.wikipedia.org/wiki/DALL-E

   e. DALL·E, DALL·E 2, and DALL·E 3 (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.

6. Image tracing - Wikipedia

   en.wikipedia.org/wiki/Image_tracing

   If the image is not yet in machine readable form, then it has to be scanned into a usable file format. Once there is a machine-readable bitmap, the image can be imported into a graphics editing program (such as Adobe Illustrator, CorelDRAW, or Inkscape). Then a person can manually trace the elements of the image using the program's editing ...

7. Text-to-image personalization - Wikipedia

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

   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.

8. Transformer (deep learning architecture) - Wikipedia

   en.wikipedia.org/wiki/Transformer_(deep_learning...

   Tokenizers, which convert text into tokens. Embedding layer, which converts tokens and positions of the tokens into vector representations. Transformer layers, which carry out repeated transformations on the vector representations, extracting more and more linguistic information. These consist of alternating attention and feedforward layers.

9. Digital image processing - Wikipedia

   en.wikipedia.org/wiki/Digital_image_processing

   Digital image processing is the use of a digital computer to process digital images through an algorithm. [1][2] As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such ...