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The extracted key-frames are used to compose a single image summary.
In this article, we focused on the image reduction and image summary.
Based on bidirectional similarity measure of the patches, Simakov et al. [13] proposed an image summary algorithm.
A single image summary composed of several foreground visual objects is built based on the importance of each frame.
Because bidirectional similarity algorithm takes into consideration the completeness and coherence between the resized image and the original image, it can get image summary effectively by iteration computation.
A quantitative measurement is defined for assessing the quality of the image summary by investigating both its reconstruction ability and its representativeness of the original image set in large size.
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Here, in the form of annotated ortho-rectified (i.e. scale-consistent) satellite images, a summary of the maps found in the literature is presented, together with the results of simple spatial query designed to refine the accuracy of previously-estimated Last Glacial Maximum (LGM) ice extents.
Now, rather than simply being presented with a list of video images and summaries, the Vimeo allows you to watch those videos directly within the inbox itself.
Headlines, images, and summaries will be presented in a card format, and if you see something that interests you, you tap on the card to read the full article.
In summary, image quality, speed and functional imaging are intrinsically connected.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com