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53 results for “Multispectral imaging”
Avian-eye-inspired perovskite artificial vision system for foveated and multispectral imaging
<p>Avian eyes possess a deep central fovea as a result of extensive evolution. Deep fovea efficiently refracts incident light, creating a magnified image of the target object and making it easier to track its motion. These features are essential for detecting and tracking remote objects in dynamic environments. Furthermore, avian eyes respond to a wide spectrum of light, including visible and ultraviolet light, allowing them to efficiently distinguish the target object from complex backgrounds. Despite notable advances in artificial vision systems that mimic animal vision, the exceptional object detection and targeting capabilities of avian eyes via foveated and multispectral imaging remain underexplored. Here, we present an artificial vision system that capitalizes on these aspects of avian vision. We introduce an artificial fovea and vertically-stacked perovskite photodetector arrays whose designs are optimized by theoretical simulations for the demonstration of foveated and multispectral imaging. The artificial vision system successfully identifies colored and mixed-color objects and detects remote objects through foveated imaging. The potential for use in uncrewed aerial vehicles that need to detect, track, and recognize distant targets in dynamic environments is also discussed. Our avian-eye-inspired perovskite artificial vision system marks a notable advance in bio-inspired artificial visions.</p>
New Imaging Biomarkers for Muscular Diseases - Multispectral Optoacoustic Imaging in Spinal Muscular Atrophy
ClinicalTrials.gov study NCT04115475. IPD Sharing: YES. Countries: 1. Publications: 1.
Avian-eye-inspired perovskite artificial vision system for foveated and multispectral imaging
Open the record for dataset details and reuse information.
High Throughput Multispectral Image Processing with applications in Food Science
<p>Raw image samples for the PLoS ONE paper entitled "High Throughput Multispectral Image Processing with applications in Food Science".</p> <p>Segmented images for the PLoS ONE paper entitled "High Throughput Multispectral Image Processing with applications in Food Science".</p>
Fusion of Single and Integral Multispectral Aerial Images
<p>Abstract: <span>An adequate fusion of the most significant salient information from multiple input channels is essential for many aerial imaging tasks. While multispectral recordings reveal features in various spectral ranges, synthetic aperture sensing makes occluded features visible. We present a first and hybrid (model- and learning-based) architecture for fusing the most significant features from conventional aerial images with the ones from integral aerial images that are the result of synthetic aperture sensing for removing occlusion. It combines the environment’s spatial references with features of unoccluded targets that would normally be hidden by dense vegetation. Our method outperforms state-of-the-art two-channel and multi-channel fusion approaches visually and quantitatively in common metrics, such as mutual information, visual information fidelity, and peak signal-to-noise ratio. The proposed model does not require manually tuned parameters, can be extended to an arbitrary number and arbitrary combinations of spectral channels, and is reconfigurable for addressing different use cases. We demonstrate examples for search and rescue, wildfire detection, and wildlife observation.</span> <strong><br></strong></p>
Hullerbusch beech forest, Germany, captured by UAV-based multispectral imaging
<p>This data set contains data products of a multispectral UAV survey over the Hullerbusch beach forest, located in southern Mecklenburg–Western Pomerania, Germany. As survey drone, the DJI M300 with RTK antenna was employed and the multispectral image data was captured with a Micasense Altum multispectral camera. Data were processed in Agisoft Metashape 1.7, with the orthomosaic converted to reflectance.</p> <p>Data products: <br> Orthomosaic 5band reflectance 3.1 cm (.tif)<br> Orthomosaic RGB preview 10 cm (.tif)<br> DSM 3.1 cm (.tif)<br> RGB Dense Point Cloud 110 mio pts (.laz)<br> Agisoft Processing report (.pdf)<br> Flight shapefile (.kml)<br> <br> Center coordinates: 53.322907N, 13.441929E<br> Coordinate reference system: WGS84/UTM zone 32N<br> Survey area: 88503 m2</p> <p>Agisoft Metashape average camera location error estimates:<br> X: 13.6 cm; Y: 55.9 cm; Z: 7.2 cm; Total error: 58.1 cm<br> </p>
Online Fusion of Multi-resolution Multispectral Images with Weakly Supervised Temporal Dynamics
<p>This is the data set for experiments of satellite images of Oroville dam site in paper: Online Fusion of Multi-resolution Multispectral Images with Weakly Supervised Temporal Dynamics. Inside the zip file, there are 3 folders: 'HD-IMG-Database-Landsat-8', 'HD-IMG-Database-Landsat-8-Qest' and 'MODIS_250'.</p>
OPTIMA - RGB colour images and multispectral images (including LabelImg annotations)
<p>The images and annotations (LabelImg) in this folder are acquired during the H2020 OPTIMA project. The images were acquired in orchards, vineyards and fields in three European countries (France, Italy, Spain). The images represent three diseases in three crops: apple scab in apple, alternaria in carrot, downy mildew in grape. The txt files contain the bounding box locations for the diseases (bounding box detection for YOLOv5 object detection). </p> <p>The folder contains three subfolders:</p> <ol> <li>apple_applescab <ol> <li>ms: multispectral images acquired on 10-05-2022 in Spain with the Silios multispectral camera</li> <li>rgb: rgb colour images acquired on 27-05-2021 and 10-06-2021 in Spain with the NEON-202B-JT2-X smart-camera</li> </ol> </li> <li>carrot_alternaria <ol> <li>ms: multispectral images acquired on 23-09-2021 and 24-09-2021 in France with the Silios multispectral camera</li> <li>rgb: rgb colour images acquired on 02-09-2021, 24-09-2021, and 04-11-2021 in France with the NEON-201B-JT2-X smart-camera</li> </ol> </li> <li>grape_downymildew <ol> <li>ms: multispectral images acquired on 06-06-2019 in Italy with the IMEC multispectral camera</li> <li>rgb: rgb colour images acquired on 23-07-2021 in Italy with the NEON-201B-JT2-X smart-camera</li> </ol> </li> </ol>
Non-invasive Imaging of Muscle Structure in Duchenne Muscular Dystrophy Using Multispectral Optoacoustic Tomography
ClinicalTrials.gov study NCT03490214. IPD Sharing: NO. Countries: 1. Publications: 1.
Multispectral drone images of cocoa agroforestry in Cote d'Ivoire - Raw images
<p>This repository hosts the raw multispectral imagery dataset from drone surveys of cocoa production plots in the Central-West Region of Côte d'Ivoire.</p><p>The dataset encompasses high-resolution multispectral images from 10 cocoa production plots. These images were captured using the DJI Phantom 4 Multispectral (P4M) drone, fitted with an array of sensors capable of capturing data in RGB, red, green, blue, red edge, and near-infrared bands. </p><p>The study area comprises diverse cocoa agroforestry systems, recorded to reflect the varying structural complexities and stages of growth within the plots.</p><p>All imagery was acquired during UAV flights on May 4 and 5, 2022, between the hours of 10 AM and 2 PM (UTC). These flights were carefully scheduled to ensure optimal lighting conditions and minimal shadow interference, conducive to high-quality data capture. The region's tropical climate, marked by consistent temperatures and regular rainfall, adds to the relevance of this dataset for agricultural and ecological studies.</p><p> </p>
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.
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>
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>
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.
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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.
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.