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A Deep Learning-Based Framework for Social Data Sensing and Fusion for Enterprise Management
2022
Mathematical Problems in Engineering
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for enterprise management society based on multisource data. ...
The study designs a multilayer convolutional neural network model to process the data and proposes a recommendation path for the implementation of user data services for the enterprise management society ...
Conclusions is study proposes a semantic-oriented metadata model, combined with the classification of user needs, and constructs an enterprise management social data fusion framework based on multisource ...
doi:10.1155/2022/3606469
fatcat:ept3h5ydojfk5pdpkfhu44kr6i
Developing natural resources database with Nigeriasat-1 satellite data and geographical information systems
2012
Egyptian Journal of Remote Sensing and Space Sciences
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The result shows that the geospatial data infrastructure-based management system can provide a robust decision support tool in a holistic, cost-effective and time-saving manner that will enhance the administration ...
There have not been any foremost efforts to embrace the geospatial-based data derived from remote sensing satellite and geographical information systems (GIS) and global positioning system (GPS) into the ...
Acknowledgements The National Space Research and Development Agency (NASRDA) of Nigeria is acknowledged for providing the Nigeriasat-1 satellite data; Dr. S.O. Mohammed, Dr. G. Agbaje and Dr. H.A. ...
doi:10.1016/j.ejrs.2012.04.002
fatcat:ezq6dvcj7nadnonb4j7ymxgqka
A Survey of Methods and Technologies for Congestion Estimation Based on Multisource Data Fusion
2021
Applied Sciences
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Multisource data fusion increases the accuracy and provides a comprehensive estimation of the performance of traffic flow on a road network. ...
Various types of data collection technologies have different advantages and disadvantages as well as data characteristics, such as accuracy, sampling frequency, and geospatial coverage. ...
The funding institutions had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. ...
doi:10.3390/app11052306
fatcat:f5sj4c2alvbgnl3vsswxzrxjnu
Big Data and Its V's with IoT to Develop Sustainability
2021
Scientific Programming
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Such data can then be further utilised for smarter decisions and postanalysis for different purposes. ...
Various approaches are in practice for the recovery problem of data, such as spatiotemporal correlation and interpolation. These are used for data correlation and characteristics of sensory data. ...
To address this problem, the research proposed a new federated tensor mining (FTM) system to combine multisource mining data in order to provide security for tensorbased mining. ...
doi:10.1155/2021/3780594
fatcat:oj3tndlva5enbgbmiws45ax2ay
Big Data and cloud computing: innovation opportunities and challenges
2016
International Journal of Digital Earth
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At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. ...
cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big ...
Acknowledgements We thank the anonymous reviewers for their insightful comments and reviews. Dr George Taylor reviewed a previous version of this manuscript. ...
doi:10.1080/17538947.2016.1239771
fatcat:qbcgqj2pcvbgja6dnnakoj2saa
Advances in remote sensing applications for urban sustainability
2016
Euro-Mediterranean Journal for Environmental Integration
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The analysis identifies three key trends in the existing literature: (a) the integration of heterogeneous remote sensing data, primarily for investigating or modelling urban environments as a complex system ...
, (b) the development of new algorithms for effective extraction of urban features, and (c) the improvement in the accuracy of traditional spectral-based classification algorithms for addressing the spectral ...
The authors would also like to thank Mr Mohammed Salih and Mrs Amera Ali for a useful discussion on the applications of urban remote sensing. ...
doi:10.1007/s41207-016-0007-4
fatcat:lqtm3fzalzbdfiy5aegzhdzhia
A Blocky and Layered Management Schema for Remote Sensing Data
2020
IEEE Access
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Finally, Kylin is used to build a cube model to discuss the information mining analysis changes in the new data management model. ...
INDEX TERMS Data management, Google S2, HBase, remote sensing data. This work is licensed under a Creative Commons Attribution 4.0 License. ...
The authors would like to thank the anonymous reviewers for their valuable comments. ...
doi:10.1109/access.2020.2997519
fatcat:jvtnnfuambb5lctwl4tchra244
ExtremeEarth Meets Satellite Data From Space
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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that enables scalable data processing, machine learning, and deep learning on Copernicus data, and development of very large training datasets for deep learning architectures targeting the classification ...
Bringing together a number of cutting-edge technologies that range from storing extremely large volumes of data all the way to developing scalable machine learning and deep learning algorithms in a distributed ...
His work focuses on distributed tools for the transformation of large volumes of data in the RDF model and interlinking techniques for linked geospatial data. ...
doi:10.1109/jstars.2021.3107982
fatcat:fxmpayska5bvlj7ibw3peqhuzu
Assessment of remote sensing-based classification methods for change detection of salt-affected areas (Biskra area, Algeria)
2017
Journal of Applied Remote Sensing
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employing Landsat imagery, ancillary and multisource ground truth data. ...
Given the limited access to field data, appropriate methods were assessed for the identification and change detection of salt-affected areas, involving image interpretation and automated classifications ...
the provided data and collaboration. ...
doi:10.1117/1.jrs.11.016025
fatcat:eglqxncrmrfanag2nnw46dw4ze
Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review
[article]
2022
arXiv
pre-print
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aperture radar-optical, and RS-Geospatial Big Data fusion. ...
Furthermore, We collect and summarize some valuable resources for the sake of the development in multimodal RS data fusion. ...
Apparently, multimodal RS data fusion include multisource data fusion and multitemporal data fusion. ...
arXiv:2205.01380v1
fatcat:5btxnj5e5rf2xn65iofrh4epbu
GIS Mashups
[chapter]
2017
Encyclopedia of GIS
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Typically, we assume a parametrized covariance structure underlying the data to be modeled. ...
It took more than a decade from this point for the larger computer science community to investigate GPs for pattern analysis purposes. ...
This type of hierarchy is called a taxonomy or classification hierarchy (Fig. 5 ) and can be used as a basis for classification of data ('classification' Fig. 4) . ...
doi:10.1007/978-3-319-17885-1_530
fatcat:rrr5buo3zrevpigdtjwhewipvm
Use of Big Data Tools and Industrial Internet of Things: An Overview
2020
Scientific Programming
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A detailed report of these techniques and tools is needed which will help researchers to easily identify a tool for their data and take help to easily manage the data, organize the data, and extract meaningful ...
The proposed study is an endeavour toward summarizing and identifying the tools and techniques for big data used in Industrial Internet of Things. ...
45] Apache spark-based distributed self-organizing map algorithm for sensor data analysis 27 [48] Techniques of big data to smart city deployments 28 [51] A cognitive data stream mining technique ...
doi:10.1155/2020/8810634
fatcat:zs56m6aly5dd7beeao64pjzrkm
Support Vector Machine vs. Random Forest for Remote Sensing Image Classification: A Meta-analysis and systematic review
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Several machine-learning algorithms have been proposed for remote sensing image classification during the past two decades. ...
comparative analysis regarding the performances of RF and SVM classification against various parameters, such as data type, RS applications, spatial resolution, and the number of extracted features in ...
geospatial analysis [1] - [5] . ...
doi:10.1109/jstars.2020.3026724
fatcat:5de4psawjvfebhlsikwt7tazau
Interoperability, XML Schema
[chapter]
2017
Encyclopedia of GIS
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Cross-References
Cross-References Geospatial Semantic Integration Geospatial Semantic Web Geospatial Semantic Web: Applications Geospatial Semantic Web, Interoperability Geospatial Semantic Web: Personalization ...
The approaches of data mining are association, sequence-based analysis, clustering, estimation, classification, etc. ...
With this in mind, a generic framework for time series data mining has emerged. ...
doi:10.1007/978-3-319-17885-1_100625
fatcat:bgxdhdxa4bewzcggrogz56rdpi
Apache Spark Accelerated Deep Learning Inference for Large Scale Satellite Image Analytics
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Index Terms-Big data applications, high performance computing, image classification, inference mechanisms, machine learning, supervised learning. cludes overseeing all aspects of a lab wide private cloud ...
The shear volumes of data generated from earth observation and remote sensing technologies continue to make major impact; leaping key geospatial applications into the dual data and compute-intensive era ...
The use of deep convolutional neural networks extends to other applications including big data mining for search and retrieval tasks. ...
doi:10.1109/jstars.2019.2959707
fatcat:xaarxfgvwvgsxjzxpebhajxfhe
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