Search results for "Sensor fusion"

showing 4 items of 64 documents

Editorial for the Special Issue “Frontiers in Spectral Imaging and 3D Technologies for Geospatial Solutions”

2019

This Special Issue hosts papers on the integrated use of spectral imaging and 3D technologies in remote sensing, including novel sensors, evolving machine learning technologies for data analysis, and the utilization of these technologies in a variety of geospatial applications. The presented results showed improved results when multimodal data was used in object analysis.

medicine.medical_specialtyGeospatial analysisComputer sciencehyperspectral imagingSciencecomputer.software_genrehyperspectral imaging; point cloud; sensor integration; data fusion; machine learning; deep learning; classification; estimation; semantic segmentation; object detection; point cloud filteringmedicine3D-mallinnussensor integrationpoint cloud filteringdata fusionestimationbusiness.industryDeep learningspektrikuvausQHyperspectral imagingdeep learningobject detectionSensor fusionObject (computer science)Data scienceObject detectionsemantic segmentationSpectral imagingVariety (cybernetics)classificationpoint cloud filteringsegmentointikoneoppiminenmachine learningclassificationGeneral Earth and Planetary SciencesArtificial intelligencekaukokartoitusbusinesscomputerpoint cloudRemote Sensing
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Combining hyperspectral UAV and multispectral Formosat-2 imagery for precision agriculture applications

2014

Remote sensing is a key tool for precision agriculture applications as it is capable of capturing spatial and temporal variations in crop status. However, satellites often have an inadequate spatial resolution for precision agriculture applications. High-resolution Unmanned Aerial Vehicles (UAV) imagery can be obtained at flexible dates, but operational costs may limit the collection frequency. The current study utilizes data fusion to create a dataset which benefits from the temporal resolution of Formosat-2 imagery and the spatial resolution of UAV imagery with the purpose of monitoring crop growth in a potato field. The correlation of the Weighted Difference Vegetation Index (WDVI) from …

precision agricultureComputer sciencebusiness.industryUAVMultispectral imageHyperspectral imagingcomputer.software_genreSensor fusionPE&RCField (geography)Laboratory of Geo-information Science and Remote SensingWDVIunmixing-based data fusionTemporal resolutionComputer visionLaboratorium voor Geo-informatiekunde en Remote SensingArtificial intelligencePrecision agricultureSTARFMbusinesscomputerImage resolutionData integrationRemote sensing
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Real-time smoothing of car-following data through sensor-fusion techniques

2011

Abstract Observation of vehicles kinematics is an important task for many applications in ITS (Intelligent Transportation Systems). It is at the base of both theoretical analyses and application developments, especially in case of positioning and tracing/tracking of vehicles, car-following analyses and models, navigation and other ATIS (Advanced Traveller Information Systems), ACC (Adaptive Cruise Control) systems, CAS and CWS (Collision Avoidance Systems and Collision Warning Systems) and other ADAS (Advanced Driving Assistance Systems). Modern technologies supply low-cost devices able to collect time series of kinematic and positioning data with medium to very high frequency. Even more da…

sensor fusionEngineeringbusiness.industryVehicle controlControl engineeringKalman filterData fusionTracingSensor funsionSensor fusionADASNavigationcar-followingV2VInformation systemGeneral Materials ScienceKalman filterITSbusinessACCIntelligent transportation systemCruise controlCollision avoidanceSmoothingProcedia - Social and Behavioral Sciences
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Reflectance Measurement Method Based on Sensor Fusion of Frame-Based Hyperspectral Imager and Time-of-Flight Depth Camera

2022

Hyperspectral imaging and distance data have previously been used in aerial, forestry, agricultural, and medical imaging applications. Extracting meaningful information from a combination of different imaging modalities is difficult, as the image sensor fusion requires knowing the optical properties of the sensors, selecting the right optics and finding the sensors’ mutual reference frame through calibration. In this research we demonstrate a method for fusing data from Fabry–Perot interferometer hyperspectral camera and a Kinect V2 time-of-flight depth sensing camera. We created an experimental application to demonstrate utilizing the depth augmented hyperspectral data to measu…

sensor fusionreflectancekinectreflektanssioptiset ominaisuudetBiochemistryAtomic and Molecular Physics and OpticsAnalytical Chemistrymittausmenetelmäthyperspectraloptiset anturithyperspectral; depth data; kinect; sensor fusion; reflectanceCalibrationElectrical and Electronic Engineeringdepth dataInstrumentationAlgorithms
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