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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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Sensitivity of deep learning applied to spatial image steganalysis dataset

Authors: Tabares-Soto, Reinel; Arteaga-Arteaga, Harold Brayan; Mora-Rubio, Alejandro; Bravo-Ortíz, Mario Alejandro; Arias-Garzón, Daniel; Alzate-Grisales, Jesús Alejandro; Orozco-Arias, Simon; +2 Authors

Sensitivity of deep learning applied to spatial image steganalysis dataset

Abstract

Dataset used on the paper "Sensitivity of deep learning applied to spatial image steganalysis", it comes from ”Break Our Steganographic System”: The Ins and Outs of Organizing BOSS from Patrick Bas, Tomas Filler, Tomas Pevny authorship , on the compress files cover.rar corresponds to cover images in pgm files, with the respective stego image from WOW and S-UNIWARD steganographic algoritms on Wow.rar and Suniward.rar respectively, and Wownpy.rar and Suninpy.rar contained npy files of cover-stego images divided on Train, Test and Validation sets.

{"references": ["Patrick Bas, Tomas Filler, Tomas Pevny. \"Break Our Steganographic System\": The Ins and Outs of Organizing BOSS. INFORMATION HIDING, May 2011, Czech Republic. pp.59-70, ff10.1007/978-3- 642-24178-9_15ff. ffhal-00648057f"]}

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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