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303
datasets available to search
ShareScore release 0.7.1
Dataset results
303 results for “hyperspectral”
HyperspectralBlueberries: a dataset of hyperspectral reflectance images of normal and defective blueberries
<p>The <strong>HyperspectralBluberries</strong> dataset consists of hyperspectral datacubes, which were acquired by an in-house assembled benchtop line scanning system, from 420 blueberries of two categories, including 210 sound fruit and 210 samples with various defects. The fruit samples were hand-picked from a commercial orchard. Each scanning event, which was done for an array of 42 samples, yields two files in image formats .bil (band-interleaved-by-line) and .hdr (header), which store the hyperspectral raw data and associated metadata, respectively, and are both necessary for loading hyperspectral data for processing. In addition to sample scanning, a white reference was also scanned, which can be used for standardizing spectral responses. As a result, there are 22 files in the dataset, totaling about 25 GB in file size. The sample file names are descriptive, indicating the blueberry category and number information. The dataset was used for developing machine learning models for differentiating between normal and defective blueberries, achieving an overall accuracy of 96.6%. Software programs for the modeling work are publicly available at: <a href="https://github.com/vicdxxx/Blueberry-Defect-Detection-by-Hyperspectral-Imaging">https://github.com/vicdxxx/Blueberry-Defect-Detection-by-Hyperspectral-Imaging.</a></p> <p>Details about the dataset curation and modeling experiments are described in the journal article: <a href="https://www.sciencedirect.com/science/article/pii/S2772375524000789">Deng, B., Lu, Y., Stafne, E. (2024). </a><a href="https://www.sciencedirect.com/science/article/pii/S2772375524000789">Fusing Spectral and Spatial Features of Hyperspectral Reflectance Imagery for Differentiating between Normal and Defective Blueberries. Smart Agricultural Technology</a>. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.atech.2024.100473" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.atech.2024.100473</a>. If you use the dataset in published research, please consider citing the dataset or the <a href="https://doi.org/10.1016/j.ecoinf.2024.102546">journal article</a>. Hopefully, you find the dataset useful. </p>
Existing Urban Hyperspectral Reference Data
<p>This dataset supports the publication "Urban Hyperspectral Reference Data Availability and Reuse: State-of-the-Practice Review" DOI: 10.1111/phor.12508. The urban hyperspectral signatures of 9 pre-existing spectral libraries have been converted into .xlsx file formats and organized by material category. This reformatted and compiled dataset is uploaded to this open-source repository to promote FAIR (Findable, Accessible, Interoperable, Reusable) data principles and facilitate data preservation and reuse. </p>
Unmixing Autoencoder for Image Reconstruction from Hyperspectral Data
<p>The NIR handwriting imaging data and the noise simulated data of five <span>hydroxyl compounds: methanol, ethanol, 2-phenylethanol, 1-propanol, and 2-chloroethanol.</span></p>
A hyperspectral scan of a scene with a pond
<p>A hyperspectral scan of a scene with a pond</p>
A hyperspectral scan of Brighton, scene 1
<p>A hyperspectral scan of Brighton, scene 1</p>
A hyperspectral scan from a forest, scene 3
<p>A hyperspectral scan from a forest, scene 3</p>
A hyperspectral scan of a building 3
<p>A hyperspectral scan of a building 3</p>
A hyperspectral scan from a forest, scene 2
<p>A hyperspectral scan from a forest, scene 2</p>
A hyperspectral scan from a forest, scene 1
<p>A hyperspectral scan from a forest, scene 1</p>
A hyperspectral scan of a flowering cactus
<p>A hyperspectral scan of a flowering cactus</p>
Hyperspectral scan from the Brighton Pier
<p>A hyperspectral scan from the Brighton Pier, UK.</p>
A hyperspectral scan of Brighton, scene 3
<p>A hyperspectral scan of Brighton, scene 3</p>
A hyperspectral scan of Brighton, scene 2
<p>A hyperspectral scan of Brighton, scene 2</p>
A hyperspectral scan of a building 1
<p>A hyperspectral scan of a building 1</p>
A hyperspectral scan of a building 2
<p>A hyperspectral scan of a building 2</p>
Datasets used for Automatic Acquisition of Non-Saturated Hyperspectral Images
<p>data-sets acquired for studying correlation between automatic exposure times and hyper-spectral images, with the aim of devising procedures for automatic acquisition of non-saturated hyper-spectral images</p>
Spectral data for direct detection and quantification of phycocyanin in sediments by hyperspectral imaging: Standard calibration
<p>Accompanying data to publication: <strong>Direct detection and quantification of phycocyanin in sediments by hyperspectral imaging</strong></p> <p>Hyperspectral data with all their processing steps - normalization, ROI, subsets, masking - resulting in RABD indices of Chlorophyll a and Phycocyanin pigments from spiking experiments on sediments.</p>
Spectral data for direct detection and quantification of phycocyanin in sediments by hyperspectral imaging: Spiking Session 1 - Phycocyanin & Chlorophyll a
<p>Accompanying data to publication: <strong>Direct detection and quantification of phycocyanin in sediments by hyperspectral imaging</strong></p> <p>Hyperspectral data with all their processing steps - normalization, ROI, subsets, masking - resulting in RABD indices of Chlorophyll a and Phycocyanin pigments from spiking experiments on sediments.</p>
Spectral data for direct detection and quantification of phycocyanin in sediments by hyperspectral imaging
<p>Accompanying data to publication: <strong>Direct detection and quantification of phycocyanin in sediments by hyperspectral imaging</strong></p> <p>Excel files include hyperspectral indices of Chlorophyll a and Phycocyanin pigments from spiking experiments on sediments.</p> <p>Scripts used for producing plots in the publication and supplementary material are available on Renku; see the Software section.</p> <p>Hyperspectral data are submitted separately due to their size; see the Related works.</p>
Spectral data for direct detection and quantification of phycocyanin in sediments by hyperspectral imaging: Spiking Session 2 - Phycocyanin
<p>Accompanying data to publication: <strong>Direct detection and quantification of phycocyanin in sediments by hyperspectral imaging</strong></p> <p>Hyperspectral data with all their processing steps - normalization, ROI, subsets, masking - resulting in RABD indices of Chlorophyll a and Phycocyanin pigments from spiking experiments on sediments.</p>
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.