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154 results for “multispectral”
Supplementary Tables Novel Quantitative Methods to Enable Multispectral Identification of High-Purity Water Ice Exposures on Mars using High Resolution Imaging Science Experiment Images
<p>Data describing the list of images, error and uncertainty calculations for Novel Quantitative Methods to Enable Multispectral Identification of High-Purity Water Ice Exposures on Mars using High Resolution Imaging Science Experiment Images.</p>
Assessment of Tissue Oxygenation Using Multispectral Imaging
ClinicalTrials.gov study NCT03516864. IPD Sharing: UNDECIDED. Countries: 0. Publications: 9.
Evaluation of Therapeutic Response in Spinal Muscular Atrophy Using Multispectral Optoacoustic Tomography (MSOT) and Magnetic Resonance Imaging (MRI)
ClinicalTrials.gov study NCT04262570. IPD Sharing: YES. Countries: 1. Publications: 0.
A Study of Tumor Imaging With Multispectral Optoacoustic Tomography
ClinicalTrials.gov study NCT05488483. IPD Sharing: YES. Countries: 2. Publications: 0.
High-resolution residual dry matter (RDM) map for a California oak savanna/annual grassland derived from drone multispectral remote sensing imagery and in-situ grass biomass data
Open the record for dataset details and reuse information.
Data from: Human retinal pigment epithelium: in vivo cell morphometry, multispectral autofluorescence, and relationship to cone mosaic
Open the record for dataset details and reuse information.
TROPICS03 L2B Deep Multispectral INtensity (DMIN) of Tropical cyclones estimator Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The Deep Multispectral INtensity of TCs estimator with 183 GHz brightness temperatures (D-MINT183), developed at the University of Wisconsin/CIMSS, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). D-MINT183 is a convolutional neural network (CNN) with no inherent physical understanding of TC intensity relationships, which is an approach that differs from the other two TROPICS TC Intensity algorithm (i.e., TCIE and HISA). D-MINT183 is trained using combinations of 183±1 and 183±3 GHz imagery from SSMIS, ATMS, MHS, and AMSU-B, as well as 15 hours of infrared imagery (in 3-h increments) and scalar predictors. TROPICS has 184.41 GHz and 186.51 GHz imagery, which is used as a proxy for the 183±1 GHz and 183±3 GHz imagery.
TROPICS01 L2B Deep Multispectral INtensity (DMIN) of Tropical Cyclones Estimator Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The Deep Multispectral INtensity of TCs estimator with 183 GHz brightness temperatures (D-MINT183), developed at the University of Wisconsin/CIMSS, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). D-MINT183 is a convolutional neural network (CNN) with no inherent physical understanding of TC intensity relationships, which is an approach that differs from the other two TROPICS TC Intensity algorithm (i.e., TCIE and HISA). D-MINT183 is trained using combinations of 183±1 and 183±3 GHz imagery from SSMIS, ATMS, MHS, and AMSU-B, as well as 15 hours of infrared imagery (in 3-h increments) and scalar predictors. TROPICS has 184.41 GHz and 186.51 GHz imagery, which is used as a proxy for the 183±1 GHz and 183±3 GHz imagery.
TROPICS05 L2B Deep Multispectral INtensity (DMIN) of Tropical Cyclones Estimator Algorithm V0.2
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The Deep Multispectral INtensity of TCs estimator with 183 GHz brightness temperatures (D-MINT183), developed at the University of Wisconsin/CIMSS, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). D-MINT183 is a convolutional neural network (CNN) with no inherent physical understanding of TC intensity relationships, which is an approach that differs from the other two TROPICS TC Intensity algorithm (i.e., TCIE and HISA). D-MINT183 is trained using combinations of 183±1 and 183±3 GHz imagery from SSMIS, ATMS, MHS, and AMSU-B, as well as 15 hours of infrared imagery (in 3-h increments) and scalar predictors. TROPICS has 184.41 GHz and 186.51 GHz imagery, which is used as a proxy for the 183±1 GHz and 183±3 GHz imagery.
TROPICS06 L2B Deep Multispectral INtensity (DMIN) of Tropical Cyclones Estimator Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The Deep Multispectral INtensity of TCs estimator with 183 GHz brightness temperatures (D-MINT183), developed at the University of Wisconsin/CIMSS, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). D-MINT183 is a convolutional neural network (CNN) with no inherent physical understanding of TC intensity relationships, which is an approach that differs from the other two TROPICS TC Intensity algorithm (i.e., TCIE and HISA). D-MINT183 is trained using combinations of 183±1 and 183±3 GHz imagery from SSMIS, ATMS, MHS, and AMSU-B, as well as 15 hours of infrared imagery (in 3-h increments) and scalar predictors. TROPICS has 184.41 GHz and 186.51 GHz imagery, which is used as a proxy for the 183±1 GHz and 183±3 GHz imagery.
Multispectral Imagery, NDVI, and Terrain Models, Big Trail Lake, Fairbanks, AK, 2019
This dataset provides multispectral reflectance imagery (green at 550 nm, red at 660 nm, red edge at 735 nm, and near-infrared at 790 nm), normalized difference vegetation index (NDVI), and digital surface and terrain models for a 0.5 km2 area surrounding Big Trail Lake (BTL) in the Goldstream Creek Valley north of Fairbanks, Alaska. These high spatial resolution maps (13 cm x 13 cm) were generated by unmanned aerial vehicle (UAV) imagery collected on 2019-08-04. Raw images (n=908) were combined into mosaic layers that incorporated ground control points with centimeter accuracy. These layers were then used to generate vegetation, water body, and elevation maps and then combined with in situ measurements of methane flux to improve upscaling models of greenhouse gas emissions.
TROPICS07 L2B Deep Multispectral INtensity (DMIN) of Tropical Cyclones Estimator Algorithm V0.2
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The Deep Multispectral INtensity of TCs estimator with 183 GHz brightness temperatures (D-MINT183), developed at the University of Wisconsin/CIMSS, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). D-MINT183 is a convolutional neural network (CNN) with no inherent physical understanding of TC intensity relationships, which is an approach that differs from the other two TROPICS TC Intensity algorithm (i.e., TCIE and HISA). D-MINT183 is trained using combinations of 183±1 and 183±3 GHz imagery from SSMIS, ATMS, MHS, and AMSU-B, as well as 15 hours of infrared imagery (in 3-h increments) and scalar predictors. TROPICS has 184.41 GHz and 186.51 GHz imagery, which is used as a proxy for the 183±1 GHz and 183±3 GHz imagery.
Identification of Prognostic Biomarkers of Ovarian High Grade Serous Carcinoma through Spatial Transcriptome Analysis and Multispectral imaging
GEO Series GSE279969. Homo sapiens. 69 samples. Type: Other.
Fusion of Single and Integral Multispectral Aerial Images
<p>We present a novel hybrid (model- and learning-based) architecture for fusing the most significant features from conventional aerial images and integral aerial images that result from synthetic aperture sensing for removing occlusion caused by dense vegetation. It combines the environment's spatial references with features of unoccuded targets. Our method out-beats the state-of-the-art, does not require manually tuned parameters, can be extended to an arbitrary number and combinations of spectral channels, and is reconfigurable to address different use-cases. </p>
Prediction of Yield and Nitrogen-Use Efficiency by Using Consumer-Grade Unmanned Aerial Vehicle Multispectral Images of Winter Wheat
<p>It contains supplementary materials(revised version)and supporting data of Tables of Prediction of Yield and Nitrogen-Use Efficiency by Using Consumer-Grade Unmanned Aerial Vehicle Multispectral Images of Winter Wheat.<em> </em>However, the artical has not published. Data is available upon request.</p> <p>If you need anything, please don't hesitate to contact me(liujk@ahstu.edu.cn).</p>
DL models trained for multispectral tree trunk types detection and segmentation
<p>This repository holds Deep Learning (DL) models (YOLOv5 Small and YOLOv8 Small) that were trained to perform multispectral (4-channel RGB-NIR images) tree trunk types detection and segmentation in forested environments.</p>
Video: Integrating Multispectral Imaging, Reflectance Transformation Imaging (RTI), and Photogrammetry for Archaeological Objects
<p>Video of talk presented remotely at the session "Illumination of Material Culture Symposium II" at Digital Heritage 2018 on October, 26, 2018. A method for combining multiple forms of imagery, including RTI and Multispectral Imaging, with 3D models is summarized and illustrated by still images and animation.</p>
PI Data: Multispectral and Thermal Surface Imagery and Surface Elevation Mosaics (CAMSPEC-AIR)
<p>This data set contains high-resolution image products (orthomosaics) acquired from midsized uncrewed aerial systems that have been processed for value-added quality. The instrument itself, a multispectral imager, the Altum by Micasense, captures six spectral bands (red, green blue, NIR, red edge, and LWIR/thermal1) as radiance, which is converted to reflectance. The code used to develop these images first uses tools from the Micasense Python library2 to apply dark level corrections, row gradient corrections, and radiometric corrections. Next, it uses the processing API from Agisoft Metashape software to align and mosaic the processed imagery, following the processes developed by the USGS' structure from motion workflow documentation.3 Captures at different altitudes (recorded in MSL) produce an orthomosaic, a tif image containing information related to the six spectral bands, and a digital elevation model (DEM), a tif image containing information related to the elevation of the surveyed terraine. Metadata included in every image can be used to extract lat, lon, and reflectance values.</p>
Data for: Novel Quantitative Methods to Enable Multispectral Identification of High-Purity Water Ice Exposures on Mars from High Resolution Imaging Science Experiment (HiRISE) Images
<p>This repository contains all the HiRISE UNFILTERED products used in the paper by Rangarajan et al. (2023) titled "Novel quantitative methods to enable multispectral identification of high-purity water ice exposures using High Resolution Imaging Science Experiment (HiRISE) images" published in Icarus. </p>
Determination of Product Thickness Applied on Different Areas of the Face Using a Multispectral Imaging Method
ClinicalTrials.gov study NCT05837208. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.