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Dataset results
40 results for “digital forensics”
Dataset literature review digital forensic and male
<p>data yang digunakan untuk membuat penelitian berdasarkan tinjauan dengan kata kunci digital forensic and male</p>
(PDF-like) An Ontology for Supporting Digital Forensics Controlled Experiments: Early Stages of Development - Figures
<p>Figures from An Ontology for Supporting Digital Forensics Controlled Experiments: Early Stages of Development</p>
Data Set Literature Review Digital Forensic and Forensic Sciences
<p>Data ini digunakan untuk membuat penelitian sesuai dengan tinjauan literatur dengan kata kunci "<em>Digital Forensic</em>" dan "<em>Forensic Sciences</em>"</p>
Dataset Literature Review Digital Forensic and Forensic Anthropology Population Data
<p>Data ini dipergunakan untuk membuat penelitian sesuai dengan Tinjauan Literatur dengan kata kunci "<em>Digital Forensik</em> dan <em>Forensic Anthropology Population Data"</em></p>
Dataset Literature Review Digital Forensic AND Forensic Sciences
<p>Data ini digunakan untuk membuat penelitian berdasarkan tinjauan literatur dengan kata kunci "Digital Forensic" dan "Forensic Sciences"</p>
Dataset Literature Review Digital Forensic AND Forensic Anthropology Population Data
<p>Data ini digunakan untuk membuat penelitian berdasarkan tinjauan literatur dengan kata kunci "digital forensic" dan "forensic anthropology population data"</p>
Dataset Literature Review Digital Forensic
<p>data ini diambil dengan menggunakan analisis lens.org serta kata kunci digital forensic and fingerprints. dan menggunakan filter tipe dokumen jurnal artikel, subjek hukum, dan menggunakan tahun publikasi 2012-2022.</p>
Dataset - ExperDF-Onto: an Ontology for Promoting Controlled Experimentation in Digital Forensics
<p>Dataset - ExperDF-Onto: an Ontology for Promoting Controlled Experimentation in Digital Forensics</p>
photo all filter DIGITAL FORENSIC AND AUTOPSY
<p>photo all filter DIGITAL FORENSIC AND AUTOPSY</p>
data csv dan bibtex digital forensic and autopsy
<p>data csv dan bibtex digital forensic and autopsy</p>
Data Digital Forensic dan Humans
<p>Data Digital Forensic dan Humans</p>
UTS Digital Forensic, Computer-Assisted
<p>data uts digital forensic computer-assisted</p>
photos all filter by analyzing filter digital forensic and autopsy
<p>photos all filter by analyzing filter digital forensic and autopsy</p>
digital forensic AND imaging
<p>upload dari lens.org</p>
Dataset of Evaluation Survey of a Conceptual Model for Promoting Digital Forensics Experiments
<p>Dataset of Evaluation Survey of a Conceptual Model for Promoting Digital Forensics Experiments</p>
Dataset of Experimentation in Digital Forensics: an State of the Art Analysis
<p>Dataset of Experimentation in Digital Forensics: an State of the Art Analysis</p>
Dataset Literature Review Digital Forensic AND Methods
<p>Data yang saya upload adalah data yang mana diambil dari lens.org dengan memasukkan keyword/kata kunci “Digital Forensic” “Methods” pada Scholarly Works lalu akan muncul banyak jumlah Scholarly Works yang kemudian sesuai instruksi saya filter sebanyak 3 kali.<br> Yang pertama, saya filter pada bagian Document Type = Journal Articel, selanjutnya yang kedua filter Years = 2012-2022, dan yang ketiga adalah pada bagian Subject,Subject Matter = Law.<br> Yang mana disetiap melakukan filter saya mengekspor data dalam 2 bentuk yaitu, Csv dan BibTex sekaligus menyimpan gambar Analysis Data yang tertera.</p>
Dataset Literature Review Digital Forensic AND Methods
<p>Data ini diambil dari website lens.org dengan memasukkan keyword/kata kunci “Digital Forensic” “Methods” pada Sholarly Works yang kemudian difilter sebanyak 3 kali. yang pertama di filter pada bagian Document Type yaitu pada “Journal Articel”. kedua, di filter pada Years yang mana data rate 10 tahun sebelumnya yaitu mulai tahun 2012 sampai dengan tahun 2022. dan yang terakhir di filter pada bagian Subject, Subject Matter “Law”. Pada setiap tahapan mulai awal hingga akhir semua data tersebut di export dengan format CSV dan BIBTEX. Kemudian semua data yang udah terkumpul akan digunakan untuk membuat penelitian sesuai dengan Literature Review dengan kata kunci Digital Forensic AND Methods.</p>
The Digital Forensics 2023 dataset - DF2023
<p>For a detailed description of the DF2023 dataset, please refer to:<strong> </strong></p> <pre><code> @inproceedings{Fischinger2023DFNet, title={DF2023: The Digital Forensics 2023 Dataset for Image Forgery Detection}, author={David Fischinger and Martin Boyer}, journal={The 25th Irish Machine Vision and Image Processing conference. (IMVIP)}, year={2023} } </code></pre> <p>DF2023 is a dataset for image forgery detection and localization. The training and validation datasets contain 1,000,000/5,000 manipulated images (and the ground truth masks).</p> <p>The DF2023 training dataset comprises:</p> <ul> <li>100K forged images produced by removal (inpainting) operations</li> <li>200K images produced by enhancement modifications</li> <li>300K copy-move manipulated images and</li> <li>400K spliced images</li> </ul> <p> </p> <p><strong>=== Naming convention === </strong></p> <p>The naming convention of DF2023 encodes information about the applied manipulations. Each image name has the following form:</p> <p><strong>COCO_DF_0123456789_NNNNNNNN.{EXT}</strong> (e.g. <em>COCO_DF_E000G40117_00200620.jpg</em>)</p> <p>After the identifier of the image data source ("<em>COCO</em>") and the self-reference to the Digital Forensics ("<em>DF</em>") dataset, there are 10 digits as placeholders for the manipulation. Position <em>0</em> defines the manipulation types copy-move, splicing, removal, enhancement ([C,S,R,E]). The following digits 1-9 represent donor patch manipulations. For positions [1,2,7,8] (resample, flip, noise and brightness), a binary value indicates if this manipulation was applied to the donor image patch. Position 3 (rotate) indicates by the values 0-3 if the rotation was executed by 0, 90, 180 or 270 degrees. Position 4 defines if <em>BoxBlur </em>(B) or <em>GaussianBlur </em>(G) was used. Position 5 specifies the blurring radius. A value of 0 indicates that no blurring was executed. Position 6 indicates which of the Python-PIL contrast filters <em>EDGE ENHANCE</em>, <em>EDGE ENHANCE MORE</em>, <em>SHARPEN</em>, <em>UnsharpMask</em> or <em>ImageEnhance </em>(values 1-5) was applied. If none of them was applied, this value is set to 0. Finally, position 9 is set to the JPEG compression factor modulo 10, a value of 0 indicates that no JPEG compression was applied. The 8 characters <em>NNNNNNNN</em> in the image name template stand for a running number of the images.</p> <p> </p> <p><strong>=== Terms of Use / Licence ===</strong></p> <p>The DF2023 dataset is based on the MS COCO dataset. Therefore, rules for using the images form MS COCO apply also for DF2023:</p> <blockquote> <p>Images</p> <p>The COCO Consortium does not own the copyright of the images. Use of the images must abide by the <a href="https://www.flickr.com/creativecommons/">Flickr Terms of Use</a>. The users of the images accept full responsibility for the use of the dataset, including but not limited to the use of any copies of copyrighted images that they may create from the dataset.</p> </blockquote>
Dataset Literatur Review Digital Forensic AND Methods
<p>Data tersebut didapatkan dengan menggunakan website lens.org dengan memilih Scholarly Works dan pencariannya berbasis kata kunci/keyword “Digital Forensic” “Methods” dan akan memunculkan sejumlah data yang didalamnya berbentuk dokumen. Yang selanjutnya di filter sebanyak 3 kali yang mana fitur filter pertama yaitu pada bagian Document Type “Journal Article”, selanjutnya menggunakan fitur filter date range yang mana menggunakan data rate 10 tahun sebelumnya yaitu tahun 2012 sampai dengan tahun 2022, yang terakhir menggunakan fitur filter Subject Matter pada Subject “Law”. Adapun pada setiap tahapan mulai awal hingga akhir semua data tersebut masing-masing di export dengan format CSV dan BIBTEX, dan diambil semua gambar yang muncul pada menu analisys di lens.org pada tahap terakhir.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.