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1,832 results for “Cameras”

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zenodo44/100

Multiple DJI drone flights with hyperspectral camera over forests in Lithuania #3

<p>Hyperspectral data in all of the datasets consist of processed hyperspectral data cubes to radiance values.<br>all data cubes with _radiance.dat and ._radiance.hdr files are for ENVI format data file. While _rect.dat and _rect.hdr files are ENVI files with georectification applied.</p> <p>Hyperspectral data also contain calculated RGB and NDVI png and tiff images. Png images are generated from _radiance.dat files and tiff images are generated from _rect.dat files that have georectification.</p> <p>All hyperspectral data was collected using the Specim hyperspectral pushbroom camera.</p> <p>&nbsp;</p> <p>### Hyper 3</p> <p>https://art21-icaerus.s3.eu-central-1.amazonaws.com/Hyper_3.zip</p> <p>Dataset consists of 7 flight lines filmed over an infected forest.</p> <p>Each flight folder denoted by fl# contains processed hyperspectral data cubes and "processed" folder with RGB and NDVI images.&nbsp;</p> <p>Dataset zip size: 33.6 GB</p>

opencc-by-4.0Sep 2024View details →
zenodo44/100

Multiple DJI drone flights with hyperspectral camera over forests in Lithuania #2

<p>Hyperspectral data in all of the datasets consist of processed hyperspectral data cubes to radiance values.<br>all data cubes with _radiance.dat and ._radiance.hdr files are for ENVI format data file. While _rect.dat and _rect.hdr files are ENVI files with georectification applied.</p> <p>Hyperspectral data also contain calculated RGB and NDVI png and tiff images. Png images are generated from _radiance.dat files and tiff images are generated from _rect.dat files that have georectification.</p> <p>All hyperspectral data was collected using the Specim hyperspectral pushbroom camera.</p> <p>&nbsp;</p> <p>### Hyper 2</p> <p><a href="https://art21-icaerus.s3.eu-central-1.amazonaws.com/Hyper_1.zip/Hyper_2.zip">https://art21-icaerus.s3.eu-central-1.amazonaws.com/Hyper_2.zip</a></p> <p>Dataset consists of 7 flight lines filmed over an infected forest.</p> <p>Each flight folder denoted by fl# contains processed hyperspectral data cubes and "processed" folder with RGB and NDVI images.&nbsp;</p> <p>Dataset zip size: 23.4 GB</p>

opencc-by-4.0Sep 2024View details →
zenodo44/100

Multiple DJI drone flights with hyperspectral camera over forests in Lithuania #1

<p>Hyperspectral data in all of the datasets consist of processed hyperspectral data cubes to radiance values.<br>all data cubes with _radiance.dat and ._radiance.hdr files are for ENVI format data file. While _rect.dat and _rect.hdr files are ENVI files with georectification applied.</p> <p>Hyperspectral data also contain calculated RGB and NDVI png and tiff images. Png images are generated from _radiance.dat files and tiff images are generated from _rect.dat files that have georectification.</p> <p>All hyperspectral data was collected using the Specim hyperspectral pushbroom camera.</p> <p>&nbsp;</p> <p><a title="Hyperspectral imaging dataset over Lithuanian forests " href="https://art21-icaerus.s3.eu-central-1.amazonaws.com/Hyper_1.zip">https://art21-icaerus.s3.eu-central-1.amazonaws.com/Hyper_1.zip</a></p> <p>Dataset consists of 6 flight lines filmed over a stated healthy forest.</p> <p>Each flight folder denoted by fl# contains processed hyperspectral data cubes and "processed" folder with RGB and NDVI images.&nbsp;</p> <p>Dataset zip size: 25.9 GB</p>

opencc-by-4.0Sep 2024View details →
zenodo44/100

Sparse camera volumetric video applications. A comparison of visual fidelity, user experience, and adaptability: Subjective fidelity study data

<p>Supplementary Material to the Paper: <em>Sparse camera volumetric video applications. A comparison of visual fidelity, user experience, and adaptability</em></p> <p>This folder contains all collected data and scripts that were used to analyze the subjective fidelity study.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Codes and test datasets developed for Mapping paleolacustrine deposits with a UAV-borne multispectral camera: Implications for future drone mapping on Mars.

<p>NASA&rsquo;s Ingenuity Mars Helicopter has ushered in a new era in planetary exploration by utilizing Unmanned Aerial Vehicles (UAVs) to enhance our understanding of planetary surfaces. This project evaluates the potential of UAVs for mapping Martian environments, using Lake Natron, Tanzania, as an analog for Martian paleolakes.</p> <p>During two field seasons (January and July 2023), we employed a Phantom 4 Pro drone equipped with a MicaSense RedEdge-M multispectral camera and a TerraSpec Halo VNIR-SWIR spectrometer to capture high-resolution imagery and spectral data. Almost all image processing and analysis were performed using Python scripting, except for image mosaic and Digital Elevation Model (DEM) generation.</p> <p>We benchmarked the onboard image processing capabilities using a Raspberry Pi 5 single-board computer.&nbsp;</p> <p>In this repository, we share all the code developed during our study. Processing steps include,<br>1. DN to radiance conversion<br>2. Panel radiance extraction<br>3. Calculate reflectance factors using DLS data<br>4. Calculate reflectance at MicaSense band<br>5. Convert radiance to reflectance using 1 point empirical line method (1p ELM)<br>6. Convert radiance to reflectance using 2 point empirical line method (2p ELM)<br>7. Atmospheric correction using 6SV method<br>8. Convert radiance to reflectance using DLS data<br>9. Calculate Band indices<br>10. Weighted Kmean clustering<br>11. Finding the optimal number of clusters using the elbow method<br>12. Cmean clustering</p> <p>We also included sample image data used in the study. Feel free to contact us for more information/data.</p>

openmit-licenseOct 2024View details →
zenodo44/100

Mars 2020 Perseverance SHERLOC WATSON camera pre-delivery characterization and calibration image data

<p>The data presented here include images acquired by the&nbsp;WATSON&nbsp;(Wide Angle Topographic&nbsp;Sensor for Operations and eNgineering) camera during pre-delivery characterization and calibration testing at Malin Space Science Systems (MSSS, San Diego, California, USA) in September and October 2019. They also include video documentation of the camera&rsquo;s dust cover motion. WATSON is one of two imaging subsystems of the SHERLOC (Scanning Habitable Environments with Raman &amp; Luminescence for Organics &amp; Chemicals) instrument onboard NASA&rsquo;s Mars 2020 Perseverance rover which landed in Jezero crater, Mars, in February 2021.</p> <p>These data accompany the instrument calibration and characterization report by Edgett et al. (2019) and the WATSON characteristics reported by Bhartia et al. (2021). The image data presented here are listed and described in the Appendix to Edgett et al. (2019), which is also available here with the data.</p> <p>References cited:</p> <p>Bhartia, R., L. W. Beegle, L. DeFlores, W. Abbey, J. Razzell Hollis, K. Uckert,&nbsp;B. Monacelli, K. S. Edgett, M. R. Kennedy, M. Sylvia, D. Aldrich, M. Anderson,&nbsp;S. A. Asher, Z. Bailey, K. Boyd, A. S. Burton, M. Caffrey, M. J. Calaway, R. Calvet,&nbsp;B. Cameron, M. A. Caplinger, B. L. Carrier, N. Chen, A. Chen, M. J. Clark, S. Clegg,&nbsp;P. G. Conrad, M. Cooper, K. N. Davis, B. Ehlmann, L. Facto, M. D. Fries, D. H. Garrison, D. Gasway, F.&nbsp;T. Ghaemi, T. G. Graff, K. P. Hand, C. Harris, J. D. Hein, N. Heinz,&nbsp;H. Herzog, E. Hochberg, A. Houck, W. F. Hug, E. H. Jensen, L. C. Kah, J. Kennedy,&nbsp;R. Krylo, J. Lam, M. Lindeman, J. McGlown, J. Michel, E. Miller, Z. Mills, M. E. Minitti,&nbsp;F. Mok, J. Moore, K. H. Nealson, A. Nelson, R. Newell, B. E. Nixon, D. A. Nordman,&nbsp;D. Nuding, S. Orellana, M. Pauken, G. Peterson, R. Pollock, H. Quinn, C. Quinto,&nbsp;M. A. Ravine, R. D. Reid, J. Riendeau, A. J. Ross, J. Sackos, J. A. Schaffner,&nbsp;M. Schwochert, M. O Shelton, R. Simon, C. L. Smith, P. Sobron, K. Steadman, A. Steele, D. Thiessen, V.&nbsp;D. Tran, T. Tsai, M. Tuite, E. Tung, R. Wehbe, R. Weinberg,&nbsp;R. H. Weiner, R. C. Wiens, K. Williford, C. Wollonciej, Y.-H. Wu, R. A. Yingst, J. Zan (2021)&nbsp;Perseverance&rsquo;s Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals&nbsp;(SHERLOC) investigation, Space Science Reviews 217, 58. https://doi.org/10.1007/s11214-021-00812-z</p> <p>Edgett, K. S., M. A. Caplinger, M. A. Ravine (2019) Mars 2020 Perseverance SHERLOC WATSON Camera Pre-delivery Characterization and Calibration Report, Malin Space Science Systems, San Diego, California.&nbsp;https://doi.org/10.13140/RG.2.2.18447.00165</p>

opencc-by-4.0Jul 2021View details →
zenodo44/100

Electron backscatter patterns from Nickel acquired with varying camera gain

<p>Ten electron backscatter diffraction (EBSD) datasets from a recrystallized, polycrystalline sample of nickel. The datasets, each comprising 29 800 patterns, were collected from the same region of interest (ROI) with EBSD camera gains varying from 0 dB to 24 dB (camera maximum). A backscattered electron image of the ROI is also included.</p> <p>The data was acquired in order to study denoising of EBSD patterns, more specifically the increased signal-to-noise ratio obtained after principal component analysis followed by dimensionality reduction, as presented in H W &Aring;nes, J Hjelen, B E S&oslash;rensen, A T J van Helvoort, K Marthinsen &quot;Processing and indexing of electron backscatter patterns using open-source software,&quot; IOP Conf. Ser.:Mater. Sci. Eng. (2019), doi:<a href="https://doi.org/10.1088/1757-899X/891/1/012002">10.1088/1757-899X/891/1/012002</a>. This conference paper is part of the proceedings of EMAS 2019 - 16th European Workshop on Modern Developments and Applications in Microbeam Analysis held in Trondheim, Norway. However, the data is released with the hope that it can be used to compare the performance of denoising methods in general.</p> <p>The datasets, Pattern.dat, are stored in the NORDIF (binary) format, with the top-left pixel in the top-left pattern as the first byte, and the bottom-right pixel in the bottom-right pattern as the last byte. They can be opened in for example the open-source Python package kikuchipy (https://github.com/pyxem/kikuchipy). Assuming Python 3.7 or above and the package is installed, the patterns in scan 1 can be read and plotted with the following commands:</p> <pre><code class="language-python">import kikuchipy as kp s = kp.load('/path/to/nickel_scan_gain/scan1_gain0db/Pattern.dat') s.plot()</code></pre> <p>&nbsp;</p>

opencc-by-4.0Sep 2019View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-28 Exp. 001 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise of single air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness)&nbsp;separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected into the 2D setup through a straw (4 mm diam). Frame rate of the high speed camera is 1000 fps.&nbsp;The&nbsp;spherical mirror used for the Schlieren setup was 75 mm wide with&nbsp;a 750 mm focal length.</p>

opencc-by-4.0Mar 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-28 Exp. 004 - Part 2 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of multiple&nbsp;air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water and particles (with ~0.1-0.3 mm diameter). The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam) at high speed. Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Mar 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-28 Exp. 004 - Part 1 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of multiple&nbsp;air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water and particles (with ~0.1-0.3 mm diameter). The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam) at high speed. Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Mar 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-28 Exp. 003 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of multiple&nbsp;air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam) at high speed. Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Mar 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-28 Exp. 002 - Part 1 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of multiple&nbsp;air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam). Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Mar 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-28 Exp. 002 - Part 2 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of multiple&nbsp;air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam). Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Mar 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-29 Exp. 002 - Part 3 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of three coalescing air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam) at high speed. Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Apr 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-29 Exp. 002 - Part 4 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise of some&nbsp;coalescing air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam) at high speed. Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Apr 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-29 Exp. 002 - Part 2 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of two coalescing air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam) at high speed. Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Apr 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-29 Exp. 001 - Part 2 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of multiple&nbsp;air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam) at high speed. Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Apr 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-29 Exp. 001 - Part 1 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of multiple&nbsp;air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam) at high speed. Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Apr 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-29 Exp. 002 - Part 1 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the rise&nbsp;of multiple&nbsp;air bubbles in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with distilled water. The gap between the two parallel sheets is 3 mm. Air was injected manually into the 2D setup through a straw (4 mm diam) at high speed. Frame rate of the high speed camera is 250 fps. The spherical mirror used for the Schlieren setup was 75 mm wide with a 750 mm focal length.</p>

opencc-by-4.0Apr 2023View details →
zenodo44/100

ENDGAME - Laboratory Experiment 2022-11-29 Exp. 005 - Part 2 - High Speed Camera data

<p>Preliminary test with high speed camera and Schlieren shadow photography.</p> <p>Images of the injection of air in a 2D setup obtained using&nbsp;2 parallel glass sheets (3 mm thickness) separated by rubber seals and filled with a viscous fluid. The viscous fluid is obtained mixing distilled water with a hair gel (2/3 distilled water, 1/3 hair gel). The gap between the two parallel sheets is 3 mm. Air was injected into the 2D setup through a capillary tube (~2&nbsp;mm diam) with constant flow rate (~13x10<sup>-3&nbsp;</sup>l/s). Frame rate of the high speed camera is 250 fps. The spherical mirror has been covered in order to acquire only optical images and compare them&nbsp;with the corresponding Schlieren shadow photography images (ENDGAME_LabExp_HighSpeedCamera_20221129_003_XXX and ENDGAME_LabExp_HighSpeedCamera_20221129_004_XXX).</p>

opencc-by-4.0Jun 2023View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record