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Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology
[article]
2020
arXiv
pre-print
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With the aim of providing a comprehensive overview for researchers who are interested in developing a deep-learning-based analysis system for power lines inspection data, this paper conducts a thorough ...
Following the typical procedure of inspection data analysis, we categorize current works in this area into component detection and fault diagnosis. ...
Therefore, they improved the procedure and proposed a fault diagnosis method based on the ensemble learning with multi-level perception. ...
arXiv:2003.09802v1
fatcat:2ywazixc2vfq7c35pgzci5gmgq
Hybrid Wavelet Stacking Ensemble Model for Insulators Contamination Forecasting
2021
IEEE Access
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ACKNOWLEDGMENT The authors are thankful to the Coordination for the Improvement of Higher Education Personnel (CAPES), awarding a doctoral scholarship to one of the authors. ...
Equipment that assesses the condition of insulators in the system based on the image can be harmed by interference from solar radiation. ...
With a higher level of contamination, fungi can settle on the surface of the insulator, as can be seen in Figure 1B . ...
doi:10.1109/access.2021.3076410
fatcat:573oewdr2vaafapybskmopnudu
PV System Predictive Maintenance: Challenges, Current Approaches, and Opportunities
2020
Energies
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return-on-investment and minimize time to warranty claim in PV installations. ...
Given the size of the problem and gaps with current solutions, the authors propose that PV system owners need an unbiased third-party off-the-shelf system-level predictive maintenance tool to optimize ...
Predictive Maintenance Based on Machine Learning and Forecasting In general, this approach is moderately expensive and offers a medium amount of detection accuracy. ...
doi:10.3390/en13061398
fatcat:r6t6ybrczrerdnsiwvrrmbn4ga
Blending Colored and Depth CNN Pipelines in an Ensemble Learning Classification Approach for Warehouse Application Using Synthetic and Real Data
2021
Machines
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The use of a synthetic dataset improved accuracy, precision, recall and f1-score in comparison with models trained only on the real domain. ...
The methodology consists of fine-tuning several CNNs on Red–Green–Blue (RBG) and Red–Green–Blue-Depth (RGB-D) synthetic and real datasets, using the best architecture of each domain in a blended ensemble ...
Conflicts of Interest: The funders 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/machines10010028
fatcat:ilvsxyrbjrb2lcza6lzqia5dma
2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70
2021
IEEE Transactions on Instrumentation and Measurement
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Article numbers are based on specified topic areas and corresponding codes associated with the publication. ...
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021. ...
., +, TIM 2021 3512210 Dual-Ensemble Multi-Feedback Neural Network for Gearbox Fault Diagnosis. ...
doi:10.1109/tim.2022.3156705
fatcat:dmqderzenrcopoyipv3v4vh4ry
Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges
2019
IEEE Access
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Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached. ...
Smart UAVs are the next big revolution in UAV technology promising to provide new opportunities in different applications, especially in civil infrastructure in terms of reduced risks and lower cost. ...
A UAV with Tetracam multi-spectral camera was deployed to take aerial image for crop. ...
doi:10.1109/access.2019.2909530
fatcat:xgknpyuqazhpvferjkkdohxmtu
Program
2021
2021 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)
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This motivated the need for new emerging trends such as Edge, Fog, and Pervasive Computing, where we merge hierarchical computing with efficient communication, leveraging learning-based distributed optimization ...
We will discuss state-of-the-art contributions we have recently published regarding distributed inference/classifications in IoT, and multi-drone systems, taking into consideration privacy and mobility ...
for Tree Detection in Aerial Images of Rural Areas In this paper, we propose a study to evaluate how saliency methods can highlight and support the segmentation of trees in aerial images.An analysis of ...
doi:10.1109/ccece53047.2021.9569199
fatcat:35c7o6f6svc5rgnyhjpbvjp7iy
Program
2022
2022 International Conference on Decision Aid Sciences and Applications (DASA)
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A maximum of 92.90% classification accuracy is obtained using the features of IMF-4 with 10-fold cross-validation. The results conclude that the proposed method can detect AD patients efficiently. ...
The proposed method can further be used to detect other neurological disorders. ...
This paper presents an Internet of Things (IoT) based CO2 gas level monitoring and automated decision-making system inside a smart factory using the unmanned aerial vehicle (UAV) and multi-access edge ...
doi:10.1109/dasa54658.2022.9765271
fatcat:ttqppf4j3navnaxe653mrzmezi
Program
2021
2021 National Conference on Communications (NCC)
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In the final section, advanced concepts related to the use of modern machine learning and deep learning algorithms on automotive radar data for varied applications such as pedestrian detection, object ...
The following part of the tutorial will cover the fundamentals of radar detection with a focus on the ubiquitous Neyman-Pearson detection rule, the likelihood ratio test and the constant false alarm rate ...
In this paper, we have suggested a new transfer-learning-based automatic ALL detection method. ...
doi:10.1109/ncc52529.2021.9530194
fatcat:ahdw5ezvtrh4nb47l2qeos3dwq
Comparative Analysis of Different Machine Learning Classifiers for the Prediction of Chronic Diseases
[chapter]
2022
Comparative Analysis of Different Machine Learning Classifiers for the Prediction of Chronic Diseases
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A comparative study of different machine learning classifiers for chronic disease prediction viz Heart Disease & Diabetes Disease is done in this paper. ...
Precise diagnosis of these diseases on time is very significant for maintaining a healthy life. ...
The region-based segmentation will segment the data dependent on the taken-out features using GLCM algorithm. ...
doi:10.13052/rp-9788770227667
fatcat:da47mjbbyzfwnbpde7rgbrlppe
Conference Digest
2020
2020 IEEE Aerospace Conference
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Learning Algorithms are combined in an ensemble to improve accuracy. ...
We report on a new Multi-Frame Blind Deconvolution (MFBD) implementation developed to reconstruct high resolution images of Low Earth Orbit (LEO) satellites from short-exposure ensembles of images recorded ...
ADTM combines Self-Organizing Maps (SOMs) as the basis for modeling system behavior with supervised machine learning techniques for localizing detected anomalies. ...
doi:10.1109/aero47225.2020.9172613
fatcat:ioqf5ijrx5gvffu3ls34aa2nsq
Defense Advanced Research Projects Agency (Darpa) Fiscal Year 2019 Budget Estimates
2018
Zenodo
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Efforts focus on identified medical gaps in warfighter carerelated to health monitoring and preventing the spread of infectious disease. ...
through cellular,tissue, organ, and whole organism levels. ...
Accomplishments/Planned Programs ($ in Millions) FY 2017 FY 2018 FY 2019 Title: Aerial Dragnet Description: Aerial Dragnet seeks to detect multiple small Unmanned Aerial Systems (UAS) in complex and/or ...
doi:10.5281/zenodo.1215599
fatcat:kxduvg6a5nflhf6iilkwnolobu
Engineering, Technology & Applied Science Research (ETASR), Vol. 11, No. 2, pp. 6845-7068
[article]
2021
Zenodo
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The journal was first published in February 2011. ISSN: 1792-8036 and 2241-4487. ...
Engineering, Technology & Applied Science Research (ETASR) is an international bimonthly wide scope, peer-reviewed open access journal for the publication of original articles concerned with diverse aspects ...
ACKNOWLEDGEMENTS The authors would like to thank Yuta Kinoshita for helping in conducting the seismic response analysis. ...
doi:10.5281/zenodo.4720665
fatcat:mk2prflstjaa3bhkjenwy22s6u
Three-dimensional point-cloud room model in room acoustics simulations
2013
Journal of the Acoustical Society of America
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Detection patterns are best predicted by an optimal cuecombination model based on signal-detection theory. ...
This, in turn, eliminates the influence of higher level processes on phonetic perception in the identification task. ...
One of challenging tasks required in Bayesian model selection is the exploration of high-dimensional multi-variate spaces such that a key quantity, termed the Bayesian evidence, can be estimated in order ...
doi:10.1121/1.4806371
fatcat:ln4w6j7cjvchrckf2gzfmeiwoi
Acoustics of ancient Greek and Roman theaters in use today
2006
Journal of the Acoustical Society of America
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In this research, holographic diagnosis, a machine diag- nosis technique based on holographic approach, is introduced to find the position of faults effectively. ...
spectral-based perception. ...
This problem is analyzed by comparing the time and frequency domains solution of the ray model with models based on the wave number integration technique. ...
doi:10.1121/1.4787803
fatcat:3lczeegofreblpjmfixt7gdxv4
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