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The first sheet can be typed, drawn, or written upon. The second sheet is coated with a layer of wax that had been impregnated with one of a variety of colorants. The pressure of writing or typing on the first sheet transfers the colored wax from the second sheet to the shiny, coated back side of the first sheet, producing a mirror image.
Allan Paivio's dual-coding theory is a basis of picture superiority effect. Paivio claims that pictures have advantages over words with regards to coding and retrieval of stored memory because pictures are coded more easily and can be retrieved from symbolic mode, while the dual coding process using words is more difficult for both coding and retrieval.
Shiny is a web framework for developing web applications (apps), originally in R and since 2022 in python. It is free and open source. [2] It was announced by Joe Cheng, CTO of Posit, formerly RStudio, in 2012. [3] One of the uses of Shiny has been in fast prototyping. [4] In 2022, a separate implementation Shiny for Python was announced. [5]
In all classes of digital imaging, the information is converted by image sensors into digital signals that are processed by a computer and made output as a visible-light image. For example, the medium of visible light allows digital photography (including digital videography) with various kinds of digital cameras (including digital video cameras).
Examples of applications of such real-time holograms include phase-conjugate mirrors ("time-reversal" of light), optical cache memories, image processing (pattern recognition of time-varying images), and optical computing. The amount of processed information can be very high (terabits/s), since the operation is performed in parallel on a whole ...
For example, Ansel Adams used darkroom exposure techniques to darken and lighten photographs. Other techniques include retouching using ink or paint, airbrushing, double exposure, piecing photos or negatives together in the darkroom, and scratching instant films. Software for digital image manipulation ranges from casual to professional skillsets.
The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]
The first two example-based style transfer algorithms were image analogies [1] and image quilting. [2] Both of these methods were based on patch-based texture synthesis algorithms. Given a training pair of images–a photo and an artwork depicting that photo–a transformation could be learned and then applied to create new artwork from a new ...