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Figure 3 from: Wheeler Q, Bourgoin T, Coddington J, Gostony T, Hamilton A, Larimer R, Polaszek A, Schauff M, Solis A (2012) Nomenclatural benchmarking: the roles of digital typification and telemicroscopy. ZooKeys 209: 193-202. https://doi.org/10.3897/zookeys.209.3486
Figure 3 - Screen capture of ROBOT(E) system in use. User is able to orient specimen on multiple axes by actuating micro-step motors that position on x, y, and z scales as well as spinning around axis of pin or tilting specimen to examine lateral or ventral perspectives.
Figure 2 from: Dietrich C, Hart J, Raila D, Ravaioli U, Sobh N, Sobh O, Taylor C (2012) InvertNet: a new paradigm for digital access to invertebrate collections. ZooKeys 209: 165-181. https://doi.org/10.3897/zookeys.209.3571
Figure 2 - Current HUBzero-based InvertNet homepage showing top menu bar with content areas accessible to registered users.
Figure 3 from: Schmidt S, Balke M, Lafogler S (2012) DScan – a high-performance digital scanning system for entomological collections. ZooKeys 209: 183-191. https://doi.org/10.3897/zookeys.209.3115
Figure 3 - Enlargements of drawer images from Fig. 1 to show quality differences between image file formats. Each of the three specimens was captured in JPEG (a, d, g), TIFF (b, e, h), and RAW (c, f, i). A high resolution version of the image is available under media.zsm-entomology.de/suppl/zookeys_mass_digitisation_volume/Fig_3.png
Figure 7 from: Brecko J, Mathys A, Dekoninck W, Leponce M, VandenSpiegel D, Semal P (2014) Focus stacking: Comparing commercial top-end set-ups with a semi-automatic low budget approach. A possible solution for mass digitization of type specimens. ZooKeys 464: 1-23. https://doi.org/10.3897/zookeys.464.8615
Figure 7 - Focus stacking in Zerene Stacker. The small image in the upper corner provides a detailed close-up of 518 × 345 pix of the image at 100%. A Stack of 77 pictures, aligned and combined with PMax B Stack of 44 pictures, aligned and combined with PMax The individual pictures of both stacks are made with the Leica Z6 APO with DFC290 and Manfrotto led light system.
Figure 9 from: Brecko J, Mathys A, Dekoninck W, Leponce M, VandenSpiegel D, Semal P (2014) Focus stacking: Comparing commercial top-end set-ups with a semi-automatic low budget approach. A possible solution for mass digitization of type specimens. ZooKeys 464: 1-23. https://doi.org/10.3897/zookeys.464.8615
Figure 9 - A 3D model of a Dicranorrhina sp. beetle. The left pictures (A, C) represent the 3D model with its texture, while the right pictures (B, D) are from the model with the mesh only and show the level of detail of the 3D model made in Agisoft Photoscan.
Figure 8 from: Brecko J, Mathys A, Dekoninck W, Leponce M, VandenSpiegel D, Semal P (2014) Focus stacking: Comparing commercial top-end set-ups with a semi-automatic low budget approach. A possible solution for mass digitization of type specimens. ZooKeys 464: 1-23. https://doi.org/10.3897/zookeys.464.8615
Figure 8 - Focus stacking in Zerene Stacker. The small image in the upper corner provides a detailed close-up of 518 × 345 pix of the image at 100%. A Stack of 74 pictures, aligned and combined with PMax B Stack of 41 pictures, aligned and combined with PMax. The individual pictures of both stacks are made with the Canon-Cognisys set-up and double flash lights.
Figure 5 from: Brecko J, Mathys A, Dekoninck W, Leponce M, VandenSpiegel D, Semal P (2014) Focus stacking: Comparing commercial top-end set-ups with a semi-automatic low budget approach. A possible solution for mass digitization of type specimens. ZooKeys 464: 1-23. https://doi.org/10.3897/zookeys.464.8615
Figure 5 - The results of the different stacking methods in Zerene Stacker, each with a detail of a hairy leg and a part of the head with hairs. A, B details of the stack pictures by the PMax method C, D details of the stacked picture with the DMap method.
Figure 4 from: Brecko J, Mathys A, Dekoninck W, Leponce M, VandenSpiegel D, Semal P (2014) Focus stacking: Comparing commercial top-end set-ups with a semi-automatic low budget approach. A possible solution for mass digitization of type specimens. ZooKeys 464: 1-23. https://doi.org/10.3897/zookeys.464.8615
Figure 4 - The results of the different stacking methods in Helicon Focus: each stacking option is provided with a detail of a hairy leg and a part of the head with hairs. A, B result of Method A (average) C, D result of Method B (depth) E, F result of Method C (pyramid).
Figure 6 from: Brecko J, Mathys A, Dekoninck W, Leponce M, VandenSpiegel D, Semal P (2014) Focus stacking: Comparing commercial top-end set-ups with a semi-automatic low budget approach. A possible solution for mass digitization of type specimens. ZooKeys 464: 1-23. https://doi.org/10.3897/zookeys.464.8615
Figure 6 - Focus stacking in Zerene Stacker. The small image in the upper corner provides a detailed close-up of 518 × 345 pix of the image at 100%. A Stack of 70 pictures, aligned and combined with PMax B Stack of 41 pictures, aligned and combined with PMax. The individual pictures of both stacks are made with the Leica MZ16A with DFC500 camera and Leica KL 1500 LCD lights.
Figure 3 from: Brecko J, Mathys A, Dekoninck W, Leponce M, VandenSpiegel D, Semal P (2014) Focus stacking: Comparing commercial top-end set-ups with a semi-automatic low budget approach. A possible solution for mass digitization of type specimens. ZooKeys 464: 1-23. https://doi.org/10.3897/zookeys.464.8615
Figure 3 - The results of the different stacking methods in CombineZP: each stacking option is provided with a detail of a hairy leg and a part of the head with hairs. A, B details of the stack pictures by the Do Stack method C, D details of the stacked picture with the Do Soft Stack E, F details of the Do Weighted Stack method G, H details of the combined pictured with the Pyramid Weighted method I, J details of the stacked image with the Pyramid Do stack method K, L Details of the Stacked image with the Pyramoid Maximum Contrast method.
Figure 1 from: Brecko J, Mathys A, Dekoninck W, Leponce M, VandenSpiegel D, Semal P (2014) Focus stacking: Comparing commercial top-end set-ups with a semi-automatic low budget approach. A possible solution for mass digitization of type specimens. ZooKeys 464: 1-23. https://doi.org/10.3897/zookeys.464.8615
Figure 1 - The Canon-Cognisys set-up at the RBINS. The Canon 600D Camera, equipped with a Canon MP-E 65 mm 1:2.8 1–5× Macro Photo Lens, is mounted on the vertically positioned StackShot (Cognisys inc.). In the Ikea closet, at the bottom, you see the two Yongnuo YN560II speedlites positioned frontally and above is the plexiglas fig covered with paper to position the specimen.
Figure 2 from: Brecko J, Mathys A, Dekoninck W, Leponce M, VandenSpiegel D, Semal P (2014) Focus stacking: Comparing commercial top-end set-ups with a semi-automatic low budget approach. A possible solution for mass digitization of type specimens. ZooKeys 464: 1-23. https://doi.org/10.3897/zookeys.464.8615
Figure 2 - The results of the different stacking methods in Auto-Montage: each stacking option is provided with a single picture which is reduced in size by the Auto-Montage software itself and imprinted with watermarks. A represents the Blended Stacking option B picture composed by the Compound Weighted method C picture stacked by the Exponentially Weighted option D picture composed by the Fixed method and E picture stacked by the Weighted method.
Figure 2 from: Coleman ChO (2018) Shadings in digital taxonomic drawings. Zoosystematics and Evolution 94(2): 529-533. https://doi.org/10.3897/zse.94.28624
Figure 2 A) In Photoshop use "Magic Wand Tool" and the "shift" key to mark areas in the drawing for shading. B) Create a new layer, by clicking on second icon from the right in the icon bar at the lower end of the window. C) Select the newly created layer before applying the shading. D) Select "Brush", modify "Master Diameter" and set "Flow" at about 3–4%.
Figure 4 from: Coleman ChO (2018) Shadings in digital taxonomic drawings. Zoosystematics and Evolution 94(2): 529-533. https://doi.org/10.3897/zse.94.28624
Figure 4 A) Place pixel cloud, saved without outlines from Photoshop into Illustrator using the File-Place command. B) Move the pixel cloud in the corresponding areas of the vector graphics in Illustrator.
Figure 3 from: Coleman ChO (2018) Shadings in digital taxonomic drawings. Zoosystematics and Evolution 94(2): 529-533. https://doi.org/10.3897/zse.94.28624
Figure 3 A) In Photoshop select newly created layer and apply shading by spraying pixels onto selected areas. B) After airbrushing, make first layer, containing the outlines, invisible by clicking on eye icon in "Layers". By this only the pixel clouds are retained.
Kathmandu, Nepal. Digital Terrain Model.
<p>Kathmandu, Nepal. Digital Terrain Model.</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.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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.