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A Self-Calibrated Localization System using Chirp Spread Spectrum in a Wireless Sensor Network
2013
KSII Transactions on Internet and Information Systems
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The proposed localization system is composed of accurate ranging values that are analyzed by simple linear regression that utilizes a Big-O(n 2 ) of only a few data points and an algorithm with a self-calibration ...
To operate multiple mobile nodes concurrently, we propose a localization system with both low complexity and high accuracy and that is based on a chirp spread spectrum (CSS) radio. ...
Experimental evaluation The BSN, ANs and MNs were deployed in order to evaluate the performance of our proposed location estimation method. ...
doi:10.3837/tiis.2013.02.005
fatcat:dqyommexrrbi3e7h6gel5hxv6y
Methods of revaluation of former geodetic measurement networks
2022
Geomatics, Landmanagement and Landscape
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The effectiveness of the revaluation methods of former networks was assessed on the basis of experimental studies using data from test objects. ...
The following paper presents and evaluates three methods of improving the accuracy parameters of former registry and measurement networks. ...
The estimated accuracy of the position of the points of the tested networks was determined on the basis of displacement vectors of the test sample points (searched out network points) in relation to their ...
doi:10.15576/gll/2022.1.61
fatcat:lmhxzawztze4hjyv2i3r6lva4u
Low-Power LoRa Signal-Based Outdoor Positioning Using Fingerprint Algorithm
2018
ISPRS International Journal of Geo-Information
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We propose a LoRa signal-based positioning method that uses a fingerprint algorithm instead of a received signal strength indicator (RSSI) proximity or TDoA method. ...
The main objective of this study was to evaluate the accuracy and usability of the fingerprint algorithm for large areas in the real world. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/ijgi7110440
fatcat:us7coyb7zzgxdb7omzacouxulu
An Experimental Evaluation of Position Estimation Methods for Person Localization in Wireless Sensor Networks
[chapter]
2011
Lecture Notes in Computer Science
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The described estimators are then evaluated off-line on the experimentally collected data. ...
The goal of this paper is to present a comprehensive real-world evaluation of methods for person localization in a WSN based on received signal strength (RSS) range measurements. ...
Acknowledgment This work was supported by the German Research Foundation (DFG) within the Research Training Group GRK 1194 "Self-organizing Sensor-Actuator Networks". ...
doi:10.1007/978-3-642-19186-2_10
fatcat:7lfuq4l2kfgc7pjdqi2sotdadm
Prediction of protein stability changes for single-site mutations using support vector machines
2005
Proteins: Structure, Function, and Bioinformatics
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We evaluate our approach using cross-validation methods on a large dataset of single amino acid mutations. ...
Moreover, the experimental results show that the prediction accuracy obtained using sequence alone is close to the accuracy obtained using tertiary structure information. ...
ACKNOWLEDGMENTS Work supported by an NIH Biomedical Informatics Training grant (LM-07443-01), an NSF MRI grant (EIA-0321390), a grant from the University of California Systemwide Biotechnology Research ...
doi:10.1002/prot.20810
pmid:16372356
fatcat:ej4nvnmkanbnbi3nxkydnenmki
Unsupervised Learning for Solving RSS Hardware Variance Problem in WiFi Localization
2009
Journal on spesial topics in mobile networks and applications
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This method was designed and implemented in a working WiFi positioning system and evaluated using different WiFi devices with diverse RSS signal patterns. ...
Experimental results demonstrate that the proposed learning method improves positional accuracy within 100 s of learning time. ...
Effect of linear signal-pattern shift on the accuracy of a WiFi positioning system Before describing how this linear shift in RSS signal patterns affects the positional accuracy of a WiFi position- fingerprint ...
doi:10.1007/s11036-008-0139-0
fatcat:k7fsdthqdvdefpxb23a7bfmspi
A Study of Athlete Pose Estimation Techniques in Sports Game Videos Combining Multiresidual Module Convolutional Neural Networks
2021
Computational Intelligence and Neuroscience
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In this paper, we propose a multiresidual module convolutional neural network-based method for athlete pose estimation in sports game videos. ...
The neural network model proposed in this paper achieves high accuracy of 89.5% and 88.2% on the upper arm and lower arm, respectively, so the method in this paper reduces the influence of occlusion on ...
pose estimation algorithm views human pose detection as a key point regression problem and is trained with a large amount of data with joint point class and position annotations to finally obtain a model ...
doi:10.1155/2021/4367875
pmid:34992645
pmcid:PMC8727100
fatcat:vxqj2wz345c2bfjl36wuzvvepa
LNEMLC: Label Network Embeddings for Multi-Label Classification
[article]
2019
arXiv
pre-print
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in learning and inference of any base multi-label classifier. ...
To address these issues we propose a new multi-label classification scheme, LNEMLC - Label Network Embedding for Multi-Label Classification, that embeds the label network and uses it to extend input space ...
For each data set, we take data points from our parameter estimation experimental scenario and treat each group of parameter values as a separate observation. ...
arXiv:1812.02956v2
fatcat:d2zlvcm7k5b2pbp5ikkj64bkpi
D-VPnet: A Network for Real-time Dominant Vanishing Point Detection in Natural Scenes
[article]
2020
arXiv
pre-print
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The proposed method was tested using a public dataset and a Parallel Line based Vanishing Point (PLVP) dataset. ...
As an important part of linear perspective, vanishing points (VPs) provide useful clues for mapping objects from 2D photos to 3D space. ...
Introduction The vanishing point (VP) is the intersection of two parallel lines on an image from the viewpoint of linear perspective. ...
arXiv:2006.05407v1
fatcat:5de4andykneghb6fnnzwstnbla
Optimal Vehicle Pose Estimation Network Based on Time Series and Spatial Tightness with 3D LiDARs
2021
Remote Sensing
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However, due to the different density distributions of the point cloud, it is challenging to achieve sensitive direction extraction based on 3D LiDAR by using the existing pose estimation methods. ...
Since the network was indirectly trained through the evaluation index, it could be directly used on untrained LiDAR and showed a good pose estimation performance. ...
They first used the weighted least squares algorithm to remove outliers and proposed an obstacle pose estimation method using two linear features of straight-line fitting and right-angle fitting. ...
doi:10.3390/rs13204123
fatcat:opy7t4brknhnxbtzqrhxaw76hy
Metabolic connectivity-based single subject classification by multi-regional linear approximation in the rat
2021
NeuroImage
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The optimal classification thresholds of the correlation coefficient and distance-to-fit were found be to |r| > 0.65 and d = 4 when using Siegel's slope estimator for fitting. ...
Metabolic connectivity patterns on the basis of [18F]-FDG positron emission tomography (PET) are used to depict complex cerebral network alterations in different neurological disorders and therefore may ...
Acknowledgements The authors would like to thank the preclinical imaging team of the Nuclear Medicine Department of the LMU for their consistent commitment to the imaging tasks and their excellent documentation ...
doi:10.1016/j.neuroimage.2021.118007
pmid:33831550
fatcat:nh7idwkmrzdi7bfm62lyfac7dq
Localization Using Radial Basis Function Networks and Signal Strength Fingerprints in WLAN
2009
GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference
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Experimental results indicate that the RBF based method is an efficient approach to the location determination problem that outperforms existing techniques in terms of the positioning error. ...
Fingerprinting localization techniques provide reliable location estimates and enable the development of location aware applications especially for indoor environments, where satellite based positioning ...
In Section IV we present the WLAN experimental setup used for our performance evaluation, followed by the results regarding the positioning accuracy. ...
doi:10.1109/glocom.2009.5425278
dblp:conf/globecom/LaoudiasKP09
fatcat:wim5emejujcftoqlzbs7y2buui
A Variance Model in NRTK-Based Geodetic Positioning as a Function of Baseline Length
2020
Geosciences
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Measurements were evaluated and tested using the variance model created as a function of the baseline length, in line with the aims of the study, and the results were found to be consistent. ...
This study examines the effect of baseline length on accuracy and precision in Network Real-Time Kinematic (NRTK) positioning and develops an experimental mathematical model to express this effect. ...
Secondly, the authors would like to thank the Istanbul Water and Sewerage Administration for providing full access to ISKI CORS network data and Topnet-V software. ...
doi:10.3390/geosciences10070262
fatcat:27zmwoyrrfhurkwkhopncfq2bu
MR-CapsNet: A Deep Learning Algorithm for Image-Based Head Pose Estimation on CapsNet
2021
IEEE Access
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Head pose estimation based on a single image is a challenging endeavor because of the complex background conditions and characteristics of the human face. ...
We tested our method on the AFLW2000 and BIWI datasets obtaining mean absolute errors of 4.26% and 3.95%, respectively. ...
Flow of proposed algorithm
A. FEATURE EXTRACTION Our network is based on the network proposed by Song et al. [38] , which is a compact model for age estimation from a single image. ...
doi:10.1109/access.2021.3119615
fatcat:p6cuxdwdnzhvvgfpsjuithksna
RSS-based Indoor Positioning Using Convolutional Neural Network
2020
International Journal of Online and Biomedical Engineering (iJOE)
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This approach aims to improve accuracy by reducing the noise and the randomness of collected RSS values from a wireless sensor network. ...
Our proposed approach provides a room and grid prediction accuracies of 100% and a mean error of location estimation of 0.98 m.</span></p> ...
CNN models showed an accuracy of 100% for both room and grid predictions and a positioning mean error of 0.98m. Our positioning method introduced a positioning improvement. ...
doi:10.3991/ijoe.v16i12.16751
fatcat:mqrpcgclnffxrk2ne77rwq6iqi
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