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Any text from the border should instead be in the caption. If the border has author or license information, add it to the file's EXIF information. To crop the image yourself, use the CropTool. If cropping a JPEG, consider using a lossless cropping tool such as jpegtran. For more help, see Wikipedia:Images for cleanup.
This flag vector is necessary in order to correctly flatten nested parallelism. For example, it is used in the flattening of prefix sum to segmented scan. Flattening can increase the asymptotic work and space complexity of the original program, leading to a much less efficient result. [3]
An increase of Laravel's userbase and popularity lined up with the release of Laravel 3. [1] Laravel 4, codenamed Illuminate, was released in May 2013. It was made as a complete rewrite of the Laravel framework, migrating its layout into a set of separate packages distributed through Composer, which serves as an application-level package manager.
By default, clicking on an image will direct the viewer to the file page, which contains licensing and attribution information for the image. This is required for any non-public domain images. To change the link to the image, use |linkX=, where X is the image number. However, be careful to make sure that you only do this for public domain ...
For years in HTML, a table has always forced an implicit line-wrap (or line-break). So, to keep a table within a line, the workaround is to put the whole line into a table, then embed a table within a table, using the outer table to force the whole line to stay together. Consider the following examples: Wikicode (showing table forces line-break)
There are three variants: the flattening , [1] sometimes called the first flattening, [2] as well as two other "flattenings" ′ and , each sometimes called the second flattening, [3] sometimes only given a symbol, [4] or sometimes called the second flattening and third flattening, respectively.
Cropping is the removal of unwanted outer areas from a photographic or illustrated image. The process usually consists of the removal of some of the peripheral areas of an image to remove extraneous visual data from the picture, improve its framing, change the aspect ratio, or accentuate or isolate the subject matter from its background.
In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.