Relevant bibliographies by topics / Bayesův filtr

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  1. Journal articles
  2. Dissertations / Theses
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Academic literature on the topic 'Bayesův filtr'

Author: Grafiati
Published: 28 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "Bayesův filtr"

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Sondergaard, Thomas, and Pierre F. J. Lermusiaux. "Data Assimilation with Gaussian Mixture Models Using the Dynamically Orthogonal Field Equations. Part I: Theory and Scheme." Monthly Weather Review 141, no. 6 (2013): 1737–60. http://dx.doi.org/10.1175/mwr-d-11-00295.1.

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Abstract This work introduces and derives an efficient, data-driven assimilation scheme, focused on a time-dependent stochastic subspace that respects nonlinear dynamics and captures non-Gaussian statistics as it occurs. The motivation is to obtain a filter that is applicable to realistic geophysical applications, but that also rigorously utilizes the governing dynamical equations with information theory and learning theory for efficient Bayesian data assimilation. Building on the foundations of classical filters, the underlying theory and algorithmic implementation of the new filter are devel
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Deng, G. "Adaptive empirical Bayes filter." Electronics Letters 53, no. 21 (2017): 1398–400. http://dx.doi.org/10.1049/el.2017.1308.

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Nakabayashi, Akio, and Genta Ueno. "An Extension of the Ensemble Kalman Filter for Estimating the Observation Error Covariance Matrix Based on the Variational Bayes’s Method." Monthly Weather Review 145, no. 1 (2016): 199–213. http://dx.doi.org/10.1175/mwr-d-16-0139.1.

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Abstract This paper presents an extension of the ensemble Kalman filter (EnKF) that can simultaneously estimate the state vector and the observation error covariance matrix by using the variational Bayes’s (VB) method. In numerical experiments, this capability is examined for a time-variant observation error covariance matrix, and it is noteworthy that this method works well even when the true observation error covariance matrix is nondiagonal. In addition, two complementary studies are presented. First, the stability of a long-run assimilation is demonstrated when there are unmodeled disturba
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Tödter, Julian, and Bodo Ahrens. "A Second-Order Exact Ensemble Square Root Filter for Nonlinear Data Assimilation." Monthly Weather Review 143, no. 4 (2015): 1347–67. http://dx.doi.org/10.1175/mwr-d-14-00108.1.

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Abstract The ensemble Kalman filter (EnKF) and its deterministic variants, mostly square root filters such as the ensemble transform Kalman filter (ETKF), represent a popular alternative to variational data assimilation schemes and are applied in a wide range of operational and research activities. Their forecast step employs an ensemble integration that fully respects the nonlinear nature of the analyzed system. In the analysis step, they implicitly assume the prior state and observation errors to be Gaussian. Consequently, in nonlinear systems, the analysis mean and covariance are biased, an
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Tsyrulnikov, Michael, and Alexander Rakitko. "A Hierarchical Bayes Ensemble Kalman Filter." Physica D: Nonlinear Phenomena 338 (January 2017): 1–16. http://dx.doi.org/10.1016/j.physd.2016.07.009.

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Luft, Lukas, Federico Boniardi, Alexander Schaefer, Daniel Buscher, and Wolfram Burgard. "On the Bayes Filter for Shared Autonomy." IEEE Robotics and Automation Letters 4, no. 4 (2019): 3286–93. http://dx.doi.org/10.1109/lra.2019.2926217.

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Han, Mengyuan. "Spam filter based on naive bayes algorithm." Applied and Computational Engineering 15, no. 1 (2023): 247–52. http://dx.doi.org/10.54254/2755-2721/15/20230844.

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The widespread use of Electronic Mail (E-mail) has led to a significant increase in spam, which has severely impeded the growth and well-being of the Internet. To mitigate this issue, the implementation of email filtering techniques has become necessary, requiring the use of specific technological tools. Presently, the K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Naive Bayes (NB) algorithms are commonly used in probability statistical classification methods for email filtering. Among these, the NB algorithm is the most classical, with its rich mathematical theory as the basis, h
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Pidmohylʹnyy, O. O., O. M. Tkachenko, O. I. Holubenko, and O. V. Drobyk. "Naive Bayes Classifier as one way to filter spam mail." Connectivity 142, no. 6 (2019): 58–60. http://dx.doi.org/10.31673/2412-9070.2019.065860.

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Mahler, Ronald. "Exact Closed-Form Multitarget Bayes Filters." Sensors 19, no. 12 (2019): 2818. http://dx.doi.org/10.3390/s19122818.

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The finite-set statistics (FISST) foundational approach to multitarget tracking and information fusion has inspired work by dozens of research groups in at least 20 nations; and FISST publications have been cited tens of thousands of times. This review paper addresses a recent and cutting-edge aspect of this research: exact closed-form—and, therefore, provably Bayes-optimal—approximations of the multitarget Bayes filter. The five proposed such filters—generalized labeled multi-Bernoulli (GLMB), labeled multi-Bernoulli mixture (LMBM), and three Poisson multi-Bernoulli mixture (PMBM) filter vari
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Liu, Zongxiang, Zikang Qiu, Zhijian Gao, and Jie Zhang. "Adaptive Multi-Hypothesis Marginal Bayes Filter for Tracking Multiple Targets." Remote Sensing 16, no. 12 (2024): 2154. http://dx.doi.org/10.3390/rs16122154.

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Tracking multiple targets in the presence of unknown number of targets, missed detection, clutter, and noise is a challenging problem. To cope with this problem, a novel approach for generating the potential birth targets was developed, a mathematical model for multiple hypotheses was established, and an adaptive multi-hypothesis marginal Bayes filter is herein proposed in terms of the established mathematical model for multiple hypotheses and the novel birth approach. This filter delivers the existence probabilities of targets and their probability density functions. It uses multiple hypothes
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Dissertations / Theses on the topic "Bayesův filtr"

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Havelka, Martin. "Detekce aktuálního podlaží při jízdě výtahem." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-444988.

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This diploma thesis deals with the detection of the current floor during elevator ride. This functionality is necessary for robot to move in multi-floor building. For this task, a fusion of accelerometric data during the ride of the elevator and image data obtained from the information display inside the elevator cabin is used. The research describes the already implemented solutions, data fusion methods and image classification options. Based on this part, suitable approaches for solving the problem were proposed. First, datasets from different types of elevator cabins were obtained. An algor
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Guňka, Jiří. "Adaptivní klient pro sociální síť Twitter." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237052.

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The goal of this term project is create user friendly client of Twitter. They may use methods of machine learning as naive bayes classifier to mentions new interests tweets. For visualissation this tweets will be use hyperbolic trees and some others methods.
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Matula, Tomáš. "Techniky umělé inteligence pro filtraci nevyžádané pošty." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-236060.

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This thesis focuses on the e-mail classification and describes the basic ways of spam filtering. The Bayesian spam classifiers and artificial immune systems are analyzed and applied in this thesis. Furthermore, existing applications and evaluation metrics are described. The aim of this thesis is to design and implement an algorithm for spam filtering. Ultimately, the results are compared with selected known methods.
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Ravet, Alexandre. "Introducing contextual awareness within the state estimation process : Bayes filters with context-dependent time-heterogeneous distributions." Thesis, Toulouse, INSA, 2015. http://www.theses.fr/2015ISAT0045/document.

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Ces travaux se focalisent sur une problématique fondamentale de la robotique autonome: l'estimation d'état. En effet, la plupart des approches actuelles permettant à un robot autonome de réaliser une tâche requièrent tout d'abord l'extraction d'une information d'état à partir de mesures capteurs bruitées. Ce vecteur d'état contient un ensemble de variables caractérisant le système à un instant t, comme la position du robot, sa vitesse, etc. En robotique comme dans de nombreux autres domaines, le filtrage bayésien est devenu la solution la plus populaire pour estimer l'état d'un système de faço
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Sontag, Ralph. "Hat Bayes eine Chance?" Universitätsbibliothek Chemnitz, 2004. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200400556.

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Workshop "Netz- und Service-Infrastrukturen" Hat Bayes eine Chance? Seit einigen Monaten oder Jahren werden verstärkt Bayes-Filter eingesetzt, um die Nutz-E-Mail ("`Ham"') vom unerwünschten "`Spam"' zu trennen. Diese stoßen jedoch leicht an ihre Grenzen. In einem zweiten Abschnitt wird ein Filtertest der Zeitschrift c't genauer analysiert.
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Fredborg, Johan. "Spam filter for SMS-traffic." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-94161.

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Communication through text messaging, SMS (Short Message Service), is nowadays a huge industry with billions of active users. Because of the huge userbase it has attracted many companies trying to market themselves through unsolicited messages in this medium in the same way as was previously done through email. This is such a common phenomenon that SMS spam has now become a plague in many countries. This report evaluates several established machine learning algorithms to see how well they can be applied to the problem of filtering unsolicited SMS messages. Each filter is mainly evaluated by an
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Valová, Alena. "Optimální metody výměny řídkých dat v senzorové síti." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-318682.

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This thesis is focused on object tracking by a decentralized sensor network using fusion center-based and consensus-based distributed particle filters. The model includes clutter as well as missed detections of the object. The approach uses sparsity of global likelihood function, which, by means of appropriate sparse approximation and the suitable dictionaty selection can significantly reduce communication requirements in the decentralized sensor network. The master's thesis contains a design of exchange methods of sparse data in the sensor network and a comparison of the proposed methods in t
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Delobel, Laurent. "Agrégation d'information pour la localisation d'un robot mobile sur une carte imparfaite." Thesis, Université Clermont Auvergne‎ (2017-2020), 2018. http://www.theses.fr/2018CLFAC012/document.

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La plupart des grandes villes modernes mondiales souffrent des conséquences de la pollution et des bouchons. Une solution à ce problème serait de réglementer l'accès aux centres-villes pour les voitures personnelles en faveur d'un système de transports publics constitués de navettes autonomes propulsées par une énergie n'engendrant pas de pollution gazeuse. Celles-ci pourraient desservir les usagers à la demande, en étant déroutées en fonction des appels de ceux-ci. Ces véhicules pourraient également être utilisés afin de desservir de grands sites industriels, ou bien des sites sensibles dont
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Garcia, Elmar [Verfasser], and Tino [Akademischer Betreuer] Hausotte. "Bayes-Filter zur Genauigkeitsverbesserung und Unsicherheitsermittlung von dynamischen Koordinatenmessungen / Elmar Garcia. Gutachter: Tino Hausotte." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2014. http://d-nb.info/1054731764/34.

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Dall'ara, Jacopo. "Algoritmi per il mapping ambientale mediante array di antenne." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14267/.

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La capacità di costruire delle mappe riportanti informazioni di tipo statistico di un ambiente sconosciuto, tramite dei sensori disposti all'interno di esso, è un problema soggetto a numerose ricerche scientifiche svolte in ogni parte del mondo nelle ultime due decadi, in quanto è collegato ad innumerevoli applicazioni pratiche. Lo scopo di questo elaborato è quello di fornire una veloce introduzione teorica a tale problema, per poi proporre un metodo nuovo e più efficiente che vada a sostituire, o parzialmente completare, gli strumenti usati oggigiorno.
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Books on the topic "Bayesův filtr"

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Köhler, Bert-Uwe. Konzepte der statistischen Signalverarbeitung. Springer, 2005.

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Book chapters on the topic "Bayesův filtr"

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Sharma, Vijay Kumar, Vedant Garg, Sparsh Goel, Rohan Kapoor, and Shivansh Singh. "SMS SPAM FILTER using multinomial naïve bayes approach." In Intelligent Computing and Communication Techniques. CRC Press, 2025. https://doi.org/10.1201/9781003530176-58.

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Liang, Jiachen. "Enhancing Spam Filter Using Naive Bayes and Count Vectorizer." In Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023). Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-300-9_58.

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Virmani, Deepali, Sonakshi Vij, Abhishek Dwivedi, Ayush Chaurasia, and Vidhi Karnwal. "Spam Detection Using Naïve Bayes and Trigger-Based Filter." In International Conference on Innovative Computing and Communications. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3010-4_29.

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Hall, Mark. "A Decision Tree-Based Attribute Weighting Filter for Naive Bayes." In Research and Development in Intelligent Systems XXIII. Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-663-6_5.

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Mandal, Pranab K., and V. Mandrekar. "Bayes Formula for Optimal Filter with n-ple Markov Gaussian Errors." In Recent Developments in Infinite-Dimensional Analysis and Quantum Probability. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0842-6_17.

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Fei, Huang, and Ian Reid. "Joint Bayes Filter: A Hybrid Tracker for Non-rigid Hand Motion Recognition." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24672-5_39.

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Komma, Philippe, and Andreas Zell. "Posterior Probability Estimation Techniques Embedded in a Bayes Filter for Vibration-Based Terrain Classification." In Springer Tracts in Advanced Robotics. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13408-1_8.

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Mohanan, Gopika, Deepika Menon Padmanabhan, and G. S. Anisha. "Analyzing Random Forest, Naive Bayes, and SVM to Filter Spam Emails Across Multiple Datasets." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7985-8_34.

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Nguyen, Huu-Thien-Tan, and Duy-Khanh Le. "An Approach to Improving Quality of Crawlers Using Naïve Bayes for Classifier and Hyperlink Filter." In Computational Collective Intelligence. Technologies and Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34630-9_54.

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Prasad, Renu, Rohit Agrawal, and Himanshu Sharma. "Modified Gabor Filter with Enhanced Naïve Bayes Algorithm for Facial Expression Recognition in Image Processing." In Lecture Notes in Networks and Systems. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9756-2_36.

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Conference papers on the topic "Bayesův filtr"

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Sharma, Suraj, Ratnesh Kumar Dubey, Aravendra Kumar Sharma, Shashikant Gupta, and Nidhi Dandotiya. "An Efficient Spam Classification Filter as a Naive Bayes Classifier Web Application." In 2024 International Conference on Advances in Computing Research on Science Engineering and Technology (ACROSET). IEEE, 2024. http://dx.doi.org/10.1109/acroset62108.2024.10743587.

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Jiang, Xingchen, Jingjie Gao, Fei Hua, Yuhai Gao, Xinqi Du, and Wenqian Xu. "An Improved Probability Hypothesis Density Filter Based on Variational Bayes for Closely Spaced Multi-Target Tracking." In 2024 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2024. https://doi.org/10.1109/icspcc62635.2024.10770431.

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Kanazaki, Hirofumi, Takehisa Yairi, Kazuo Machida, Kenji Kondo, and Yoshihiko Matsukawa. "Variational Bayes Data Association Filter." In 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information. IEEE, 2007. http://dx.doi.org/10.1109/issnip.2007.4496877.

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Battistelli, Giorgio, Luigi Chisci, Lin Gao, and Daniela Selvi. "Event-triggered distributed Bayes filter." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8795966.

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Pandey, Dhruvam, and Rajshekhar Gannavarpu. "Fringe pattern defect identification using Kalman filter and machine learning." In Digital Holography and Three-Dimensional Imaging. Optica Publishing Group, 2022. http://dx.doi.org/10.1364/dh.2022.w2a.6.

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The article introduces a Kalman filter and naive Bayes classifier based machine learning model for defect identification in the noisy fringe pattern. The simulation results corroborate the performance of the proposed method.
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Garcia, E., and T. Hausotte. "P8 - Bayes-Filter für dynamische Koordinatenmessungen." In AHMT 2014 - Symposium des Arbeitskreises der Hochschullehrer für Messtechnik. AHMT - Arbeitskreis der Hochschullehrer für Messtechnik, 2014. http://dx.doi.org/10.5162/ahmt2014/p8.

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Yan, Han-Bing, and Ya-Shu Liu. "Spam filter based on incremental Bayes arithmetic." In 2011 International Conference on Electrical and Control Engineering (ICECE). IEEE, 2011. http://dx.doi.org/10.1109/iceceng.2011.6056834.

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Liu, Zong Xiang, and Xiu Jiang Tang. "Particle Implementation of Marginal Distribution Bayes Filter." In 2018 14th IEEE International Conference on Signal Processing (ICSP). IEEE, 2018. http://dx.doi.org/10.1109/icsp.2018.8652418.

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Kelestemur, Tarik, Colin Keil, John P. Whitney, Robert Platt, and Taskin Padir. "Learning Bayes Filter Models for Tactile Localization." In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020. http://dx.doi.org/10.1109/iros45743.2020.9341420.

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Mahler, Ronald P. S. "Extended first-order Bayes filter for force aggregation." In AeroSense 2002, edited by Oliver E. Drummond. SPIE, 2002. http://dx.doi.org/10.1117/12.478503.

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