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ShareScore release 0.9.0
Dataset results
17 results for “Range image”
Image of sky region around Crab obtained by JEM-X1 instrument in the energy range 3-20 keV.
<p>https://www.astro.unige.ch/cdci/astrooda_?DEC=22.0145&E1_keV=3&E2_keV=20&RA=83.633083333333&T1=2003-03-15T23%3A27%3A40.0&T2=2019-03-16T00%3A03%3A15.0&T_format=isot&detection_threshold=20&instrument=jemx&jemx_num=1&osa_version=OSA10.2&product_type=jemx_image&query_status=new&query_type=Real&radius=5&src_name=Crab&use_scws=no</p> <p> </p>
Programmatic Image Sequences for Multi-Disciplinary Applications: 16 Bit TIFF Sequences, HDR FULL RANGE
<p>This dataset is a part of the paper "Defining and Characterizing Programmatic Image Sequences for Multi-Disciplinary Applications". This download is an extended part of the "Spatio-Temporal Noise Sequences: Multipurposed Pseudo-Random Visual Test Signals" project. The main project for this can be found on GitHub <a href="https://github.com/FloFriedrich/STnoise">https://github.com/FloFriedrich/STnoise</a></p>
Images of the data brushes generated for the ApPEARS deliverable D5.1 Database of vector based brush strokes and sample prints that demonstrate the range of printed materials
<p>These images are appendices of ApPEARS deliverable D5.1 Database of vector based brush strokes and sample prints that demonstrate the range of printed materials. They show the generated data brushes.</p>
Supplementary data: Bayesian multi-exposure image fusion for robust high dynamic range ptychography
<p>Accompanying supplementary data for the paper. To download this data automatically and use the software, please refer to the details in the README of the linked github repository. </p> <p><strong>Github URL: </strong><a href="https://github.com/microscopic-image-analysis/bayes-mef"><strong>https://github.com/microscopic-image-analysis/bayes-mef</strong></a></p>
HDRIHaven: Public domain high dynamic range image dataset
<p>High quality datasets are essential for image processing research.<br> This set contains 201 high dynamic range panoramic images (360 x 180 degrees) with jpeg previews.<br> <br> The images are originally published at HDRIHaven under CC0 license / waiver:<br> - HDRIHaven: https://hdrihaven.com/<br> <br> The images are named using the SOURCE_IDX_DESCRIPTION.EXTENSION format, e.g. <br> hdrihaven_001_ahornsteig_16k.hdr.xz to ease further reference (e.g. "hdrihaven_001").</p> <p><br> <strong>HDRIHaven:</strong><br> The photos were taken and processed by Greg Zaal, and he generously published the images under CC0 license.<br> The images were originally published at https://hdrihaven.com.</p> <p>The files have Radiance HDR type and 16K resolution (16384x8192, 134Mpixel)<br> <br> <strong>Bugfix:</strong></p> <p>One file was missing from the first version (hdrihaven_200_yellow_field_16k.hdr.xz).<br> This updated version should be used instead of the original.</p> <p> </p> <p><strong>Downloading data:</strong><br> Due to the large size, the .hdr images were compressed with xz, which is not especially fast, but has a high compression ratio. <br> <br> It could be quite time consuming to download each file individually.<br> If all of the files are required, then it might be a better approach to download only the "file_list.txt",<br> and use a download manager to download the rest of the files. E.g. on Unix systems: </p> <pre><code class="language-bash">wget -i file_list.txt </code></pre> <p><br> Direct link to the file list: <a href="https://zenodo.org/record/1285800/files/file_list.txt">https://zenodo.org/record/1285800/files/file_list.txt</a></p> <p>Alternatively, zenodo_get ( <a href="https://gitlab.com/dvolgyes/zenodo_get">http://gitlab.com/dvolgyes/zenodo_get</a> ) could be used to download the whole record, e.g.<br> </p> <pre><code>zenodo_get.py 10.5281/zenodo.1285800</code></pre> <p> </p> <p><strong>Related links:</strong></p> <p>You might also be interested in: <a href="https://doi.org/10.5281/zenodo.1245790">https://doi.org/10.5281/zenodo.1245790</a> which is a similar dataset.</p>
FIGURES 13–16. Dorsal and lateral habitus images. 13 in Nomenclatural changes, new country records and range extensions of Baridinae (Coleoptera, Curculionidae) from China
FIGURES 13–16. Dorsal and lateral habitus images. 13, Pteridobaris maritima, 4.3 mm, Hong Kong. 14, Nespilobaris inflatirostris, 4.5 mm, West Qianqintang (Zhejiang). 15, Ulobaris kuchenbeisseri, 3.7 mm, Beijing. 16, Ulobaris loricata, 5.1 mm, Azuoqi Helanshan (Inner Mongolia).
FIGURES 9–12. Dorsal and lateral habitus images. 9 in Nomenclatural changes, new country records and range extensions of Baridinae (Coleoptera, Curculionidae) from China
FIGURES 9–12. Dorsal and lateral habitus images. 9, Mimophilus tragicus, 7.8 mm, West Garo Hills (India). 10, Moreobaris deplanata, 3.9 mm, Linhai (Zhejiang). 11, Pellobaris melancholica, 3.7 mm, Taipingshien (Anhui). 12, Psilarthroides czerskyi, 2.9 mm, Zhouzhi Houzhenzi (Shanxi).
FIGURES 1–4. Dorsal and lateral habitus images. 1 in Nomenclatural changes, new country records and range extensions of Baridinae (Coleoptera, Curculionidae) from China
FIGURES 1–4. Dorsal and lateral habitus images. 1, Acythogaster babaulti, 4.1 mm, Medog (Tibet). 2, Athesapeuta albisquama, 3.9 mm, Beijing. 3, Baris artemisiae, 3.6 mm, Beijing. 4, Baris pilosa, 3.8 mm, Yalujiang (Heilongjiang).
Particle Size Distribution in the 3-100 micron size range derived from an Imaging FlowCytoboy for 4 transect cruises across the Pacific Ocean
<p>Surface, Underway Imaging FlowCytobot (IFCB) differential_particle_size_distribution (PSDn, images per L per micron for each size bin) or differential_particle_volume_concentration (VDn, microliters per L per micron for each size bin) for 50 log-spaced size bins in the ~3-100 micrometer size range. Size distribution data collected from surface waters using the ship"s flowthrough system (~ 7m) during SCOPE cruises Gradients 2, 3, 4, and 5 (http://scope.soest.hawaii.edu/data/gradients/gradients.html). The IFCB triggers on both scattering and fluorescence so both living and non-living particles are included in the binned estimates. Note that the particle abundances and/or concentrations in the first few and last size bins may be underestimated. Please use care when comparing results across cruises, since different settings per cruise may result in different sensitivity and detection levels. Particle size of individual particles was calculated from estimated biovolume using the distance-map algorithm of Moberg and Sosik (2012). Particles are assumed spherical and are binned over 50 logarithmically-spaced size classes centered between 3.11 micrometers and 98.15 micrometers. See metadata in each excel spreadsheet for information on binwidth of each size class as well as other relevant information. This dataset was not converted to Carbon units. Timestamp is in UTC.</p>
FIGURE 3. SEM images. A, a in Inventory of the eastern Bering Sea sponge fauna, geographic range extensions and description of Antho ridgwayi sp. nov.
FIGURE 3. SEM images. A, a section through the complete blade of the sponge perpendicular to the surface. In the center of the sponge blade, the reticulation of acanthostrongyles is visible, towards both surfaces of the sponge blade plumose tracts of styles run towards the two surfaces ending at the ectosome. B, Large and small style, acanthostrongyles and ectosomal tylotes. C, Ectosomal tylote with microspined head detail in inset at upper right. D, Acanthostrongyle. E, Small category of toxon. F, Isochelae.
Reference Ranges for Placental Perfusion Using Magnetic Resonance Imaging (MRI)PLACENTIMAGE
ClinicalTrials.gov study NCT01092949. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Supplementary 1: Underwater photogrammetry for close-range 3D imaging of dry-sensitive objects: The case study of cephalopod beaks
<ul> <li>Technical advances in 3D imaging have contributed to quantifying and understanding biological variability and complexity. However, small, dry-sensitive objects are not easy to reconstruct using common and easily available techniques such as photogrammetry, surface scanning, or micro-CT scanning. Here we use cephalopod beaks as an example as their size, thickness, transparency, and dry-sensitive nature make them particularly challenging. We developed a new, underwater, photogrammetry protocol in order to add these types of biological structures to the panel of photogrammetric possibilities.</li> <li>We used a camera with a macro-photography mode in a waterproof housing fixed in a tank with clear water. The beak was painted and fixed on a colored rotating support. Three angles of view, two acquisitions, and around 300 pictures per specimen were taken in order to reconstruct a full 3D-model. These models were compared to others obtained with micro-CT scanning to verify their accuracy.</li> <li>The models can be obtained quickly and cheaply compared to micro-CT scanning, and have sufficient precision for quantitative inter-specific morphological analyses. Our work shows that underwater photogrammetry is a fast, non-invasive, efficient, and accurate way to reconstruct 3D models of dry-sensitive objects while conserving their shape. While the reconstruction of the shape is accurate, some internal parts cannot be reconstructed with photogrammetry as they are not visible. In contrast, these structures are visible using reconstructions based on micro-CT scanning. The mean difference between both methods is very small (10<sup>-5</sup> to 10<sup>-4</sup> mm) and is significantly lower than differences between meshes of different individuals.</li> <li>This photogrammetry protocol is portable, easy-to-use, fast, and reproducible. Micro-CT scanning, in contrast, is time-consuming, expensive and non-portable. This protocol can be applied to reconstruct the 3D shape of many other dry-sensitive objects such as shells of shellfish, cartilage, plants and other chitinous materials.</li> </ul>
Supplementary 1: Underwater photogrammetry for close-range 3D imaging of dry-sensitive objects: The case study of cephalopod beaks
Open the record for dataset details and reuse information.
Fetal Magnetic Resonance Imaging: Z-score Reference Ranges for a Large Patient Population in Normal Neuroimaging Measurement
ClinicalTrials.gov study NCT07004283. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Establishing Normal Ranges of Microcirculatory Function as Determined by CytoCam-IDF Imaging
ClinicalTrials.gov study NCT03044483. IPD Sharing: NO. Countries: 1. Publications: 0.
PHOENIX MARS SURFACE STEREO IMAGER 5 RANGE OPS V1.0
The Surface Stereo Imager (SSI) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This SSI Imaging Operations RDR data set contains range data from the Surface Stereo Imager (SSI).
PHOENIX MARS SURFACE STEREO IMAGER 5 RANGE OPS V1.0
The Surface Stereo Imager (SSI) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This SSI Imaging Operations RDR data set contains range data from the Surface Stereo Imager (SSI).
ScienceDex guides
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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.