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  2. File:Calculator icon.svg - Wikipedia

    en.wikipedia.org/wiki/File:Calculator_icon.svg

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  3. File:GNOME Calculator icon 2021.svg - Wikipedia

    en.wikipedia.org/wiki/File:GNOME_Calculator_icon...

    This work is free software; you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation; either version 3 of the License, or any later version.

  4. Point spread function - Wikipedia

    en.wikipedia.org/wiki/Point_spread_function

    By virtue of the linearity property of optical non-coherent imaging systems, i.e., . Image(Object 1 + Object 2) = Image(Object 1) + Image(Object 2). the image of an object in a microscope or telescope as a non-coherent imaging system can be computed by expressing the object-plane field as a weighted sum of 2D impulse functions, and then expressing the image plane field as a weighted sum of the ...

  5. File:Pascaline calculator.jpg - Wikipedia

    en.wikipedia.org/wiki/File:Pascaline_calculator.jpg

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  6. Image moment - Wikipedia

    en.wikipedia.org/wiki/Image_moment

    In image processing, computer vision and related fields, an image moment is a certain particular weighted average of the image pixels' intensities, or a function of such moments, usually chosen to have some attractive property or interpretation. Image moments are useful to describe objects after segmentation.

  7. File:Ti 73 Graphing Calculator.jpg - Wikipedia

    en.wikipedia.org/wiki/File:Ti_73_Graphing...

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  8. AOL Mail

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    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. Quantization (image processing) - Wikipedia

    en.wikipedia.org/wiki/Quantization_(image...

    This technique is commonly used for simplifying images, reducing storage requirements, and facilitating processing operations. In grayscale quantization, an image with N intensity levels is converted into an image with a reduced number of levels, typically L levels, where L<N. The process involves mapping each pixel's original intensity value ...