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Search results for: SUPER RESOLUTION, DEEP LEARNING, THERMAL IMAGERY, OBJECT DETECTION
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Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublicationThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublicationShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Multiple Cues-Based Robust Visual Object Tracking Method
PublicationVisual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...
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Currently Commercially Available Chemical Sensors Employed for Detection of Volatile Organic Compounds in Outdoor and Indoor Air
PublicationThe paper presents principle of operation and design of the most popular chemical sensors for measurement of volatile organic compounds (VOCs) in outdoor and indoor air. It describes the sensors for evaluation of explosion risk including pellistors and IR-absorption sensors as well as the sensors for detection of toxic compounds such as electrochemical (amperometric), photoionization and semiconductor with solid electrolyte ones....
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Triangular 3D Laser Scanning in Underwater Photogrammetry
PublicationThe use of triangular 3D laser scanning may significantly enhance the visual inspection of underwater objects. In these days of high demand for accurate information, exclusively photographic documentation is not enough, as it is geometrically flawed. The authors of this article are trying to present the rudiments of laser scanning, a modern means of measuring, which is reliable, relatively easy to use and works in accordance with...
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3D Imaging Of Underwater Objects Using Multi-Beam Data
PublicationOne of the main applications of multibeam sonars is high resolution bathymetry measurement, as well as detecting and imaging of underwater objects like shipwrecks. In order to obtain the visualisation quality good enough to allow the researcher to investigate an object in more detail, the approach relying on construction of three-dimensional model of an imaged object, e.g. consisting of nodes, edges and plane elements (facets)...
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Identification of regions of interest in video for a traffic monitoring system
PublicationA system for automatic event detection in the camera image is presented in this paper. A method of limiting a region of interest to relevant parts of the image using a set of processing procedures is proposed. Image processing includes object detection with shadow removal performed in the modified YCbCr color space instead of RGB. The proposed procedures help to reduce the complexity of image processing algorithm and result in...
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Analysis of the objects images on the sea using Dempster-Shafer Theory
PublicationThe paper presents the concept of using aerial and satellite imagery or images coming from the marine radar to identify and track vessels at sea. The acquired data were subjected to a highly advanced image analysis. The development of remote sensing techniques allows to gain a huge amount of data. These data are useful information source however usually we have to use different data mining methods to gain interested information....
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Implementation of control system and tracking objects in a Quadcopter
PublicationIn this paper, we implement a quadcopter assembly with control and navigation module. The project also includes the design of the control panel for the operator which consists of a set of the micro-controller and the glove equipped with sensors and buttons. The panel has a touch screen which displays current parameters such as vehicle status, including information about orientation and geographical coordinates. The concept of quadcopter...
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Empirical Relationship Describing Total Convective and Radiative Heat Loss in Buildings
PublicationOn the basis of theoretical considerations of convective-radiative heat transfer, a relationship was developed enabling the total convective and radiative heat flux QC+R emitted from any object at tw and its surroundings at t∞ to be calculated from known values of the surface temperature of such an object, i.e., the known temperature difference Δt=tw - t∞ and average air temperature Tav. This relationship is applied to thermal...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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A novel concept for tissue-metal detection and differentiation using an inductive proximity sensor
PublicationIn this paper a novel application of inductive proximity sensors for detection of living tissue by means of measurements of the coil impedance changes at different frequencies is described. The mathematical analyses utilizing Bessel function estimation include detected object size and its distance from a sensor. The main aim of this study is to prove the possibility of distinguishing between metal objects and living tissues. The...
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Visual Detection of People Movement Rules Violation in Crowded Indoor Scenes
PublicationThe paper presents a camera-independent framework for detecting violations of two typical people movement rules that are in force in many public transit terminals: moving in the wrong direction or across designated lanes. Low-level image processing is based on object detection with Gaussian Mixture Models and employs Kalman filters with conflict resolving extensions for the object tracking. In order to allow an effective event...
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Layered background modeling for automatic detection of unattended objects in camera images
PublicationAn algorithm for automatic detection of unattended objects in video camera images is presented. First, background subtraction is performed, using an approach based on the codebook method. Results of the detection are then processed by assigning the background pixels to time slots, based on the codeword age. Using this data, moving objects detected during a chosen period may be extracted from the background model. The proposed approach...
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The accuracy of a new approach to order determination for the Modified Prony method in swath mapping application
PublicationThis article presents the performance of a new approach to determine the model order for the modified Prony method applied to swath acoustic mapping. Key requirements for any mapping application are depth determination accuracy and angular resolution. Depth determination accuracy is strictly related to angular accuracy and geometrical relations between receiver and sources of the backscattered signal. Angular resolution determines...
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Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublicationThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
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A framework for automatic detection of abandoned luggage in airport terminal
PublicationA framework for automatic detection of events in a video stream transmitted from a monitoring system is presented. The framework is based on the widely used background subtraction and object tracking algorithms. The authors elaborated an algorithm for detection of left and removed objects based on mor-phological processing and edge detection. The event detection algorithm collects and analyzes data of all the moving objects in...
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Investigating Feature Spaces for Isolated Word Recognition
PublicationThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublicationIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Equal Baseline Camera Array—Calibration, Testbed and Applications
PublicationThis paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative...
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Performance Analysis of the OpenCL Environment on Mobile Platforms
PublicationToday’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of...
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Cartographic Representation of Route Reconstruction Results in Video Surveillance System
PublicationThe video streams available in a surveillance system distributed on the wide area may be accompanied by metadata are obtained as a result of video processing. Many algorithms applied to surveillance systems, e.g. event detection or object tracking, are strictly connected with localization of the object and reconstruction of its route. Drawing related information on a plan of a building or on a map of the city can facilitate the...
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The Effect of Cryogenic Treatment on Microstructure and Mechanical Response of AISI D3 Tool Steel Punches
PublicationRecently, deep cryogenic treatment is performed to improve the mechanical responses (wear, hardness, fatigue, and thermal conductivity) of various steel components. Researchers have tried to evaluate the eco-friendly and nontoxic process to optimize the parameters. Cold-shearing punches used to manufacture various holes that undergo severe impact loading and wear in the metal forming process. This study concerns the effect of soaking...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Double Bias of Mistakes: Essence, Consequences, and Measurement Method
PublicationThere is no learning without mistakes. However, there is a clash between‘positive attitudes and beliefs’regarding learning processes and the ‘negative attitudes and beliefs’towardthese being accompanied bymistakes. Thisclash exposesa cognitive bias towardmistakesthat might block personal and organizational learning. This study presents an advanced measurement method to assess thebias of mistakes. The essence of it is the...
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Multi-Stage Video Analysis Framework
PublicationThe chapter is organized as follows. Section 2 presents the general structure of the proposed framework and a method of data exchange between system elements. Section 3 is describing the low-level analysis modules for detection and tracking of moving objects. In Section 4 we present the object classification module. Sections 5 and 6 describe specialized modules for detection and recognition of faces and license plates, respectively....
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublicationFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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Multimodal Surveillance Based Personal Protection System
PublicationA novel, multimodal approach for automatic detection of abduction of a protected individual, employing dedicated personal protection device and a city monitoring system is proposed and overviewed. The solution is based on combining four modalities (signals coming from: Bluetooth, fixed and PTZ cameras, thermal camera, acoustic sensors). The Bluetooth signal is used continuously to monitor the protected person presence, and in case...
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Tracking Moving Objects in Video Surveillance Systems with Kalman and Particle Filters – A Practical Approach
PublicationThis Chapter focuses on the first type of object tracking algorithms, namely on Kalman and particle filters. A theory of these algorithms may be found in many publications, there are also reports on implementation of these approaches to object tracking in video. However, developers of VCA systems still face two important problems. The first one is related to obtaining accurate measurements of positions and sizes of the tracked...
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CTD Gdańsk Deep_2001_2005
Open Research DataDataset includes measurements of conductivity (mS cm-1), temperature (°C), sound speed (m s-1) and salinity (PSU) made with the probe Falmouth Scientific Inc. The research was carried out in 2001 (at the turn of May and June), 2003 (beginning of May), 2005 (end of April) and in 2002 and 2004 (at the turn of September and October). In 2002, only temperature...
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Thermal Imaging Aided Assessment of a State of Equipment Under Test and its Protecting Elements
PublicationIn the paper the investigation results using thermal imaging methods are presented. The examined is a state of equipment under test and its protecting components. The estimations are done for the chosen protecting elements during surge immunity testing. The results show that the thermal imaging methods are useful for early detection of possible damage of a device being tested
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A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud
Open Research DataA new automatic and adaptive algorithm for edge extraction from a random point cloud was developed and presented herein. The proposed algorithm was tested using real measurement data. The developed algorithm is able to realistically reduce the amount of redundant data and correctly extract stable edges representing the geometric structures of a studied...
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Diagnostics of high-voltage varistor quality using resonant ultrasound spectroscopy
PublicationResonant spectroscopy is an effective nondestructive testing method focused on defects detection in tested objects. Resonance spectrum contains an information about the mechanical properties and particularly about the structural homogeneity of the whole object. A swept frequency method has been used to measure the selected resonant frequencies range. The system for measurement of resonant ultrasound spectroscopy of high-voltage...
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Naval mine detection system based of FPGA circuit
PublicationElectrochemical processes take place in a metal object immersed into sea water even if an anticorrosive coating is applied [1]. As a result, flowing field appears around the object. There are naval mines between many other objects situated in the sea. Naval mines can be put in the seabed in order to be more difficult to detect by sonars. Such a mine is located on the line demarking two environments of different electrical conductivity....
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Review of the Complexity of Managing Big Data of the Internet of Things
PublicationTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Determinanty i efekty uczenia się wydziałów ekonomicznych publicznych szkół wyższych województwa pomorskiego
PublicationPubliczne uczelnie wyższe jako twory przez lata bardzo zhierarchizowane, ze znacznymi przejawami biurokratyzmu i silnie scentralizowaną władzą, w XXI wieku mają przed sobą długą drogę w dążeniu do doskonalenia własnej zdolności do uczenia się. Głównym celem pracy było zdiagnozowanie stanu determinant i efektów uczenia się badanych organizacji. Postawiono następujące hipotezy badawcze: poziom determinant uczenia się wydziałów ekonomicznych...
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Multifrequency Nanoscale Impedance Microscopy (m-NIM): A novel approach towards detection of selective and subtle modifications on the surface of polycrystalline boron-doped diamond electrodes
PublicationIn this paper, we describe the modification of Nanoscale Impedance Microscopy (NIM), namely, a combination of contact-mode atomic force microscopy with local impedance measurements. The postulated approach is based on the application of multifrequency voltage perturbation instead of standard frequency-by-frequency analysis, which among others offers more time-efficient and accurate determination of the resultant impedance spectra...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Deep slot effect in the squirrel-cage induction motors with scalar (V/F) control
PublicationQualitative characteristics of the electrical drive considerably depend on identification accuracy of math model parameters. In particular, it is depend on detection accuracy of stator active resistance r1 that is used in calculation of flux linkages, rotary speed in sensorless control systems. Paper provides analysis of influence of stator deep slot effect to stator active resistance value
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Measurement of the temperature change of PVCP tissue phantom illuminated by dermatological laser 1.series
Open Research DataApplication of laboratory set-up for characterization of thermal properties of optical tissue phantoms during laser irradiation is presented. The produced system utilizes a thermographic camera VIGOcam v50 and a dermatological laser system with a 975 nm diode laser module. The set-up was used to perform measurements of the temporal and spatial temperature...
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Polarization-sensitive optical coherence tomography for ceramic materials inspection
PublicationCeramics production is looking for a fast, reliable and non-destructive method that can be implemented on site for defect detection and analysis. In this paper we present polarization-sensitive optical coherence tomography (PS-OCT) as a method for defect inspection. Proposed extensions to standard OCT provide additional information for complete characterization of tested object. We compare OCT and microscope imaging that can easily...
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Microstructure–Property Relationship of Polyurethane Foams Modified with Baltic Sea Biomass: Microcomputed Tomography vs. Scanning Electron Microscopy
PublicationIn this paper, novel rigid polyurethane foams modified with Baltic Sea biomass were compared with traditional petro-based polyurethane foam as reference sample. A special attention was focused on complex studies of microstructure, which was visualized and measured in 3D with high-resolution microcomputed tomography (microCT) and, as commonly applied for this purpose, scanning electron microscopy (SEM). The impact of pore volume,...
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Video Semantic Analysis Framework based on Run-time Production Rules - Towards Cognitive Vision
PublicationThis paper proposes a service-oriented architecture for video analysis which separates object detection from event recognition. Our aim is to introduce new tools to be considered in the pathway towards Cognitive Vision as a support for classical Computer Vision techniques that have been broadly used by the scientific community. In the article, we particularly focus in solving some of the reported scalability issues found in current...
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The Influence of the Cuboid Float’s Parameters on the Stability of a Floating Building
PublicationUsually, the concept of sufficient stability of a floating structure is connected with the capacity to keep a small heel angle despite the moment of heeling. The variable responsible for these characteristics is the initial metacentric height, which is the relation between the hydrostatic features of the pontoon and the mass properties of the entire object. This article answers the questions of how heavy the floating system should...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublicationDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublicationCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Deep neural networks for data analysis
e-Learning CoursesThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
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Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
PublicationIn environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical approaches. We propose a methodology called adaptive distance attention that enables us to fuse sparse, heterogeneous, and mobile sensor devices and predict values at locations with no previous measurement. The approach allows for automatically weighting the measurements according to a priori...