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325 results for “Best practices”
Fig. 3.37 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.37. Excavation site scanned with the Gotcha infrared sensor. On the left is the site without texture, on the right with texture. The excavation site pictured measures approximately 4×4 m.
Fig. 3.10 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.10. Photogrammetry model of a Costa Rican Sacrificing Warrior (800–1300 AD) in Basalt (RMAH collections). The possibility of viewing the model without the texture has improved the visibility of the belt markings. https://sketchfab.com/models/03a9c7c61cdf48c8845498d1a6b19a73
Fig. 3.9 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.9. Example of photogrammetry model of Argonauta tuberculata https://sketchfab.com/models/daed659ee685452b91d8f8c91dff761b
Fig. 3.7 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.7. Example of a photogrammetry model of an archaeological copper necklace from DRCongo https://sketchfab.com/models/122d9a4660a24f5181bc586672c9ffe3
Fig. 4.3 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 4.3. Diplopods in UV fluorescence on top, in white light in the middle, in NIR at the bottom. UV fluorescence show that diplopods can fluoresce in different ways (blue, orange or not at all). NIR show the diplopods without the external pigmented layer.
Fig. 2.30. 3D in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.30. 3D model of a mobile Palaeolithic art from "le Trou des Nutons". Above: coloured surface model; middle: Surface without texture; below: image processed with automatic filtering method to highlight surface features of bison bone. The acquisition was made with a 5 Mpx RGB machine vision camera.
Fig. 3.12 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.12. Sitophilus oryzae (3.8mm body size) scanned with DISC3D. A. Scanning scheme with 398 camera positions. B. EDOF-image from the red camera position. C. Vcm-mesh (~250k polygones). D. Textured model.
Fig. 2.31 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.31. Perisama cardases captured with PLD. The normal colour image with relighting option is found on the upper left. Upper right is the grey scale image, bottom left the normal map and bottom right algorithmically-generated sketch using a filter.
Fig. 2.28. Picture for H in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.28. Picture for H-RTI digitisation. The highlights on the black spheres allow the algorithm to reconstruct a RTI model.
Fig. 3.35 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.35. Screen capture of the Mephisto scanning software while recombining scans of a stuffed African elephant produced with the Gotcha infrared sensor.
Fig. 3.32 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.32. Ishango rod digitised with NextEngine. https://sketchfab.com/models/555f0a85ca224ab88f3712272d877ce7
Fig. 3.31 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.31. Skull of Pan paniscus (RMCA) scanned with NextEngine. Left: the mesh with texture; right: the mesh without texture. https://sketchfab.com/models/38295c2ee9dd428f93134d0e97ffe851
Fig. 3.36. 3D in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.36. 3D model of the mammoth on display at the RBINS permanent exhibition. The bones were scanned one by one at the moment the skeleton was disassembled to move it to another exhibition spot. The Gotcha infrared depth sensor was used and the different 3D models were virtually reassembled in lhpFusionBox (ULB, Brussels). https://sketchfab.com/models/2d25256368a44a0fb98d0418ac500d47
Fig. 3.34 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.34. The Primesense infrared depth sensor of the Gotcha with a tripod, allowing it to stand or be used handheld while scanning.
Fig. 2.26. Plane 5 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.26. Plane 5 of the specimen page at Zoosphere.net, showing the distribution of the specimen's species, as retrieved from GBIF. Image copyright MfN.
Fig. 2.24. Plane 3 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.24. Plane 3 of the specimen page at Zoosphere.net, showing the taxonomy of the specimen. Image copyright MfN.
Fig. 2.23. Plane 2 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.23. Plane 2 of the specimen page at Zoosphere.net, showing the specimen pictures. Image copyright MfN.
Fig. 2.11 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.11. Specimen stored within glycerin. Cleared and stained specimen of Haplochromis sp. pictured in glycerin. The right part of the picture is photographed with a magnification of 5×. Scale = 500 µm.
Fig. 2.20 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.20. Overview of the digitised specimen with the ZooSphere setup, visible at Zoosphere.net. Image copyright MfN.
Information flows around agricultural best management practices in central Pennsylvania
<p>This dataset was collected between February and April 2019, to assess the information network of agricultural Best-Management Practices (BMPs) in central Pennsylvania, a sub-region of the Chesapeake Bay watershed.</p> <p>It contains information flows (or "messages") relating to 16 specific BMPs, including:</p> <ul> <li>the BMP it relates to (e.g. riparian buffers, manure management planning, no-till, cover-cropping, etc.);</li> <li>the source and target of the information (actors);</li> <li>the kind of message (e.g. funding, regulation, technical assistance, etc.);</li> <li>the weight (strength) of messages (only for those received by farmers directly).</li> </ul> <p>Over 3900 messages/information flows were recorded, involving 57 actors.</p> <p>This data was used to conduct the study "Navigating agricultural nonpoint source pollution governance: A social network analysis of best management practices in central Pennsylvania".</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
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.