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Journal articles on the topic 'Bayesův filtr'

Author: Grafiati

Published: 28 June 2021

Last updated: 29 July 2025

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1

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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2

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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6

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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9

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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Jing, Fang Fang, and Miao Cai. "A Junk SMS Filtering Application Based on Bayes Algorithm." Applied Mechanics and Materials 513-517 (February 2014): 1197–201. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1197.

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First, this paper introduces some technology about the junk SMS filtering, analyzing the principle and model characteristics of junk SMS filtering, which are based on the Bayes Algorithm. It also gives the Simulation results and the framework process of Bayesian filter. At the same time, it proposes an improved method of the Bayesian filter, which can increase the accuracy rate. Eventually it provides the conclusion.

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Liu, Zongxiang, Junwen Luo, and Chunmei Zhou. "Multi-Hypothesis Marginal Multi-Target Bayes Filter for a Heavy-Tailed Observation Noise." Remote Sensing 15, no. 21 (2023): 5258. http://dx.doi.org/10.3390/rs15215258.

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A multi-hypothesis marginal multi-target Bayes filter for heavy-tailed observation noise is proposed to track multiple targets in the presence of clutter, missed detection, and target appearing and disappearing. The proposed filter propagates the existence probabilities and probability density functions (PDFs) of targets in the filter recursion. It uses the Student’s t distribution to model the heavy-tailed non-Gaussian observation noise, and employs the variational Bayes technique to acquire the approximate distributions of individual targets. K-best hypotheses, obtained by minimizing the neg

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Liu, Zong-xiang, Yan-ni Zou, Wei-xin Xie, and Liang-qun Li. "Multi-target Bayes filter with the target detection." Signal Processing 140 (November 2017): 69–76. http://dx.doi.org/10.1016/j.sigpro.2017.05.016.

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Brunker, Alexander, Thomas Wohlgemuth, Michael Frey, and Frank Gauterin. "Dual-Bayes Localization Filter Extension for Safeguarding in the Case of Uncertain Direction Signals." Sensors 18, no. 10 (2018): 3539. http://dx.doi.org/10.3390/s18103539.

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In order to run a localization filter for parking systems in real time, the directional information must be directly available when a distance measurement of the wheel speed sensor is detected. When the vehicle is launching, the wheel speed sensors may already detect distance measurement in the form of Delta-Wheel-Pulse-Counts (DWPCs) without having defined a rolling direction. This phenomenon is particularly problematic during parking maneuvers, where many small correction strokes are made. If a localization filter is used for positioning, the restrained DWPCs cannot process in real time. Wit

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Yunianto, Mohtar, Soeparmi Soeparmi, Cari Cari, et al. "Klasifikasi Kanker Paru Paru menggunakan Naïve Bayes dengan Variasi Filter dan Ekstraksi Ciri GLCM." INDONESIAN JOURNAL OF APPLIED PHYSICS 11, no. 2 (2021): 256. http://dx.doi.org/10.13057/ijap.v11i2.53213.

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<p class="AbstractText">Telah berhasil dilakukan klasifikasi kanker paru-paru dari 120 data citra CT Scan. Pada penelitian, proses preposisi dimulai dengan variasi filtering yaitu low pass filter, median filter, dan high pass filter. Segmentasi yang digunakan yaitu Otsu Thresholding yang kemudian teksturnya akan diekstraksi menggunakan fitur Gray Level Co-occurrence Matrix (GLCM) dengan variasi arah sudut. Hasil dari ekstraksi GLCM dijadikan database yang akan menjadi dataset untuk pengklasifikasian citra menggunakan klasifikasi naïve bayes. Hasil dari penelitian dengan 12 buah variasi d

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Mandrekar, Vidyadhar, Thilo Meyer-Brandis, and Frank Proske. "A Bayes Formula for Nonlinear Filtering with Gaussian and Cox Noise." Journal of Probability and Statistics 2011 (2011): 1–15. http://dx.doi.org/10.1155/2011/259091.

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A Bayes-type formula is derived for the nonlinear filter where the observation contains both general Gaussian noise as well as Cox noise whose jump intensity depends on the signal. This formula extends the well-known Kallianpur-Striebel formula in the classical non-linear filter setting. We also discuss Zakai-type equations for both the unnormalized conditional distribution as well as unnormalized conditional density in case the signal is a Markovian jump diffusion.

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Wang, Guoqing, Zhongxing Gao, Yonggang Zhang, and Bin Ma. "Adaptive Maximum Correntropy Gaussian Filter Based on Variational Bayes." Sensors 18, no. 6 (2018): 1960. http://dx.doi.org/10.3390/s18061960.

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18

Adisantoso, Julio, and Wildan Rahman. "Pengukuran Kinerja Spam Filter Menggunakan Graham's Naïve Bayes Classifier." Jurnal Ilmu Komputer dan Agri-Informatika 2, no. 1 (2013): 1. http://dx.doi.org/10.29244/jika.2.1.1-8.

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<p>Email spam telah menjadi masalah utama bagi pengguna dan penyedia jasa Internet. Pendekatan heuristic telah dilakukan untuk menyaring spam seperti black-listing atau rule-based filtering, namun hasilnya kurang memuaskan sehingga pendekatan berbasis konten (content-based filtering) menggunakan pengklasifikasi naïve Bayes lebih banyak digunakan saat ini. Penelitian ini bertujuan membandingkan pengklasifikasi naïve Bayes multinomial yang menggunakan atribut boolean dengan versi Graham, dan juga membandingkan kinerja dari dua metode untuk data latih, yaitu train-everything (TEFT) dan trai

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19

Jiang, Liangxiao, Lungan Zhang, Chaoqun Li, and Jia Wu. "A Correlation-Based Feature Weighting Filter for Naive Bayes." IEEE Transactions on Knowledge and Data Engineering 31, no. 2 (2019): 201–13. http://dx.doi.org/10.1109/tkde.2018.2836440.

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Kumar, Mohit, Norbert Stoll, and Regina Stoll. "Variational Bayes for a Mixed Stochastic/Deterministic Fuzzy Filter." IEEE Transactions on Fuzzy Systems 18, no. 4 (2010): 787–801. http://dx.doi.org/10.1109/tfuzz.2010.2048331.

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21

Zhou, Zihao. "The Spam Email Filter Based on the Bayes Method." Highlights in Science, Engineering and Technology 124 (February 18, 2025): 229–32. https://doi.org/10.54097/03xmee88.

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There are many spammers send a large amount of spam information to the public. The situation that spammers send spam email is common. The research from AA science have asked 55852 people, all of them claimed that spam email is becoming one part of their live. Nowadays they become used to open their mailboxes and delete the spam email. To deal with this situation people provide some filters to help people indicate which is spam email. Bayes method is one of earliest method, and up to now it still has its importance. This paper introduces the Bayes method, about the Bayesian theory and how it wo

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22

Mariyan, Richard A., Naik Prasad, A. Suhas, and G. Drakshaveni. "Naïve Bayes Filter for Communication & Enhancing Semantic in Email." International Journal of Recent Technology and Engineering (IJRTE) 9, no. 4 (2020): 282–88. https://doi.org/10.35940/ijrte.D4904.119420.

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Due tothe current pandemic of COVID-19, the world has turned into ONLINE modeand an increase in online communication thereby information exchange, sharing useful data through emails and other social Medias.So addressing the security issues places a vital role in computer security and shouldhave thepriorities. We need a security check to enhance the inbox so that the important information or emails should not reach to the spam box. In this paper to improve the filtering techniques, wehave adopted the Naïve Bayes approach in implementation and enhancing the spam filter in the email. Bayes&#

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23

Deng, Xinyi, Daniel F. Liu, Kenneth Kay, Loren M. Frank, and Uri T. Eden. "Clusterless Decoding of Position from Multiunit Activity Using a Marked Point Process Filter." Neural Computation 27, no. 7 (2015): 1438–60. http://dx.doi.org/10.1162/neco_a_00744.

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Point process filters have been applied successfully to decode neural signals and track neural dynamics. Traditionally these methods assume that multiunit spiking activity has already been correctly spike-sorted. As a result, these methods are not appropriate for situations where sorting cannot be performed with high precision, such as real-time decoding for brain-computer interfaces. Because the unsupervised spike-sorting problem remains unsolved, we took an alternative approach that takes advantage of recent insights into clusterless decoding. Here we present a new point process decoding alg

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Liu, Jiaqi, Zhen Wang, Di Cheng, Weidong Chen, and Chang Chen. "Marine Extended Target Tracking for Scanning Radar Data Using Correlation Filter and Bayes Filter Jointly." Remote Sensing 14, no. 23 (2022): 5937. http://dx.doi.org/10.3390/rs14235937.

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As the radar resolution improves, the extended structure of the targets in radar echoes can make a significant contribution to improving tracking performance, hence specific trackers need to be designed for these targets. However, traditional radar target tracking methods are mainly based on the accumulation of the target’s motion information, and the target’s appearance information is ignored. In this paper, a novel tracking algorithm that exploits both the appearance and motion information of a target is proposed to track a single extended target in maritime surveillance scenarios by incorpo

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Ng, Brenda, Kofi Boakye, Carol Meyers, and Andrew Wang. "Bayes-Adaptive Interactive POMDPs." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 1408–14. http://dx.doi.org/10.1609/aaai.v26i1.8264.

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We introduce the Bayes-Adaptive Interactive Partially Observable Markov Decision Process (BA-IPOMDP), the first multiagent decision model that explicitly incorporates model learning. As in I-POMDPs, the BA-IPOMDP agent maintains beliefs over interactive states, which include the physical states as well as the other agents’ models. The BA-IPOMDP assumes that the state transition and observation probabilities are unknown, and augments the interactive states to include these parameters. Beliefs are maintained over this augmented interactive state space. This (necessary) state expansion exacerbate

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Hendra, Asep, and Fitriyani Fitriyani. "Analisis Sentimen Review Halodoc Menggunakan Nai ̈ve Bayes Classifier." JISKA (Jurnal Informatika Sunan Kalijaga) 6, no. 2 (2021): 78–89. http://dx.doi.org/10.14421/jiska.2021.6.2.78-89.

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Healthcare service has the role to help and serve people to access medical services, i.e. providing medicines, medical consultation, or health control. Healthcare service has been transforming to a digital platform. Halodoc is one of the digital platforms that people can use for free or paid, user can also give reviews of Halodoc’s performance and services on Google Play Store to give feedback that Halodoc can use to evaluate and improve the app. The Google Play Store review is increasing every day. Therefore an analysis for the review with sentiment analysis for Halodoc’s review is needed, fi

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Hall, Mark. "A decision tree-based attribute weighting filter for naive Bayes." Knowledge-Based Systems 20, no. 2 (2007): 120–26. http://dx.doi.org/10.1016/j.knosys.2006.11.008.

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Liu, Zong-Xiang, Mian Wu, and Jie Gan. "Marginal Distribution Multi-Target Bayes Filter With Assignment of Measurements." IEEE Access 8 (2020): 118235–44. http://dx.doi.org/10.1109/access.2020.3004522.

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Zhang, Lungan, Liangxiao Jiang, and Chaoqun Li. "A New Feature Selection Approach to Naive Bayes Text Classifiers." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 02 (2016): 1650003. http://dx.doi.org/10.1142/s0218001416500038.

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Handling text data is a challenge for machine learning because text data is high dimensional in many cases. Feature selection has been approved to be an effective approach to handle high-dimensional data. Feature selection approaches can be broadly divided into two categories: filter approaches and wrapper approaches. Generally, wrapper approaches have superior accuracy compared to filters, but filters always run faster than wrapper approaches. In order to integrate the advantages of filter approaches and wrapper approaches, we propose a gain ratio-based hybrid feature selection approach to na

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Subramanian.R, Siva, Girija P, Anuradha M, Dinesh M G, Aswini J, and Divya P. "Heterogeneous Ensemble Variable Selection To Improve Customer Prediction Using Naive Bayes Model." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 5s (2023): 64–71. http://dx.doi.org/10.17762/ijritcc.v11i5s.6599.

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The analysis of customer patterns and behaviours is essential for all businesses, as the customer is the sole source of revenue. Understanding customer patterns and behavior enables businesses to enhance their business processes and customer happiness. The availability of voluminous client datasets within organizations facilitates efficient customer analysis. Yet, the inclusion of interrelated, irrelevant, as well as missing factors leads to a poor forecast of the dataset. Feature selection techniques are investigated in order to handle the problem. Objective of feature selection is to pick th

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Sokoloski, Sacha. "Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics." Neural Computation 29, no. 9 (2017): 2450–90. http://dx.doi.org/10.1162/neco_a_00991.

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In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do th

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Dong, Xiangxiang, Giorgio Battistelli, Luigi Chisci, and Yunze Cai. "A variational Bayes moving horizon estimation adaptive filter with guaranteed stability." Automatica 142 (August 2022): 110374. http://dx.doi.org/10.1016/j.automatica.2022.110374.

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LEE, CHANG-HWAN. "AN INFORMATION-THEORETIC FILTER METHOD FOR FEATURE WEIGHTING IN NAIVE BAYES." International Journal of Pattern Recognition and Artificial Intelligence 28, no. 05 (2014): 1451007. http://dx.doi.org/10.1142/s0218001414510070.

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In spite of its simplicity, naive Bayesian learning has been widely used in many data mining applications. However, the unrealistic assumption that all features are equally important negatively impacts the performance of naive Bayesian learning. In this paper, we propose a new method that uses a Kullback–Leibler measure to calculate the weights of the features analyzed in naive Bayesian learning. Its performance is compared to that of other state-of-the-art methods over a number of datasets.

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Schaffrin, B., and J. H. Kwon. "A Bayes filter in Friedland form for INS/GPS vector gravimetry." Geophysical Journal International 149, no. 1 (2002): 64–75. http://dx.doi.org/10.1046/j.1365-246x.2002.01640.x.

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Liu, Zong-xiang, Li-juan Li, Wei-xin Xie, and Liang-qun Li. "Two implementations of marginal distribution Bayes filter for nonlinear Gaussian models." AEU - International Journal of Electronics and Communications 69, no. 9 (2015): 1297–304. http://dx.doi.org/10.1016/j.aeue.2015.05.007.

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Vo, Ba-Ngu, Ba-Tuong Vo, and Dinh Phung. "Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter." IEEE Transactions on Signal Processing 62, no. 24 (2014): 6554–67. http://dx.doi.org/10.1109/tsp.2014.2364014.

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Chen, Zhenghua, Yanbing Yang, Chaoyang Jiang, Jie Hao, and Le Zhang. "Light Sensor Based Occupancy Estimation via Bayes Filter With Neural Networks." IEEE Transactions on Industrial Electronics 67, no. 7 (2020): 5787–97. http://dx.doi.org/10.1109/tie.2019.2934028.

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Xu, Wenqiang, Liangxiao Jiang, and Liangjun Yu. "An attribute value frequency-based instance weighting filter for naive Bayes." Journal of Experimental & Theoretical Artificial Intelligence 31, no. 2 (2018): 225–36. http://dx.doi.org/10.1080/0952813x.2018.1544284.

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Mukhtar, Harun, Januar Al Amien, and M. Arif Rucyat. "Filtering Spam Email menggunakan Algoritma Naïve Bayes." Jurnal CoSciTech (Computer Science and Information Technology) 3, no. 1 (2022): 9–19. http://dx.doi.org/10.37859/coscitech.v3i1.3652.

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Email atau Surat elektronik yang biasa disingkat surat-e adalah sarana kirim mengirim surat melalui jalur internet. Email spam dapat diartikan sebagai tindakan mendistribusikan pesan yang tidak diminta, seringkali dikirim secara massal menggunakan email. Email, dikirim untuk tujuan yang sah, dikenal sebagai Ham. Masalah penelitian ini ialah bagaimana memnyaring email spam yang masuk. Penelitian ini bertujuan untuk memfilter spam email secara otomatis menggunakan algoritma naïve bayes yang terhubung dengan mail server. Naïve bayes merupakan fungsi yang banyak digunakan oleh pengembang spam filt

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Cheng, Shaopeng. "Classification of Spam E-mail based on Naïve Bayes Classification Model." Highlights in Science, Engineering and Technology 39 (April 1, 2023): 749–53. http://dx.doi.org/10.54097/hset.v39i.6640.

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With the rising number of spam email, the need of more sufficient antispam filter is surging. Phishing attack can lead to extremely large losses of companies and individual, even more than 1 billion dollars in one year. This paper investigates and combines Naïve Bayes Classification and clustering algorithm in the application of identifying spam emails. With sample emails to create a dynamic dictionary containing most frequent words in spam and normal emails, this distribution of spam filter will provide a stricter method to prevent spam emails than those methods used in mail companies, e.g.,

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Qayoom, Insha, and Sameena Naaz. "Discriminant Analysis and Naïve Bayes Classifier-Based Biometric Identification Using Finger Veins." International Journal of Computer Vision and Image Processing 9, no. 4 (2019): 15–27. http://dx.doi.org/10.4018/ijcvip.2019100102.

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Finger vein identification is a dominating method of biometric technology used for authentication in a highly secure environment. Vein patterns are unique for each individual and it is underneath skin so there is less chance for forgery. In the current research work, finger vein features are extracted and verified for the purpose of authentication. The first step in this work is to pre-process the image obtained from the database. In order to get the region of interest (ROI) the threshold value is calculated using a standard deviation method followed by morphology-based functions available in

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Zhou, Xiaoliang, Donghua Wu, Zitong You, Dongyang Wu, Ning Ye, and Li Zhang. "Adaptive Two-Index Fusion Attribute-Weighted Naive Bayes." Electronics 11, no. 19 (2022): 3126. http://dx.doi.org/10.3390/electronics11193126.

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Naive Bayes (NB) is one of the essential algorithms in data mining. However, it is rarely used in reality because of the attribute independence assumption. Researchers have proposed many improved NB methods to alleviate this assumption. Among these methods, due to its high efficiency and easy implementation, the filter-attribute-weighted NB methods have received great attentions. However, there still exist several challenges, such as the poor representation ability for a single index and the fusion problem of two indexes. To overcome the above challenges, we propose a general framework of an a

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Zhang, Heng Hao, Xiu Yun Meng, and Zao Zhen Liu. "The Amalgamated Particle Filter Algorithm Based on the Bayes Theory and Used to Control Navigation’s System Interferers." Advanced Materials Research 457-458 (January 2012): 1508–13. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.1508.

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It introduces the algorithm of particle filter and the Bayes theory. The way is improved necessarily in the navigation system and then used in it. When one channel in the system is interfered and can’t work, using the changing particle’s weight factors which stand for the emanative channel in the system can control the interferer. The simulation shows the particle filter algorithm can through other channels control the interferer which occurs in the one channel. So the system also can work naturally.

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Yang, Xiu Jie, and Ping Chen. "SAR Image Denoising Algorithm Based on Bayes Wavelet Shrinkage and Fast Guided Filter." Journal of Advanced Computational Intelligence and Intelligent Informatics 23, no. 1 (2019): 107–13. http://dx.doi.org/10.20965/jaciii.2019.p0107.

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To remove the speckle noise of synthetic aperture radar (SAR) images, a novel denoising algorithm based on Bayes wavelet shrinkage and a fast guided filter is proposed. According to the statistical properties of SAR images, the noise-free signal and speckle noise in the wavelet domain are modeled as Laplace and Fisher-Tippett distributions respectively. Then a new wavelet shrinkage algorithm is obtained by adopting the Bayes maximum a posteriori estimation. Speckle noise in the high-frequency domain of SAR images is shrunk by this new wavelet shrinkage algorithm. As the wavelet coefficients of

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Liu, Zongxiang, Chunmei Zhou, and Junwen Luo. "Adaptive Marginal Multi-Target Bayes Filter without Need for Clutter Density for Object Detection and Tracking." Applied Sciences 13, no. 19 (2023): 11053. http://dx.doi.org/10.3390/app131911053.

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The random finite set (RFS) approach for multi-target tracking is widely researched because it has a rigorous theoretical basis. However, many prior parameters such as the clutter density, survival probability and detection probability of the target, pruning threshold, merging threshold, initial state of the birth object and its error covariance matrix are required in the standard RFS-based filters. In real application scenes, it is difficult to obtain these prior parameters. To address this problem, an adaptive marginal multi-target Bayes filter without the need for clutter density is propose

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Jang, Hoon-Seok, Mannan Saeed Muhammad, and Tae-Sun Choi. "Bayes Filter based Jitter Noise Removal in Shape Recovery from Image Focus." Journal of Imaging Science and Technology 63, no. 2 (2019): 20501–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2019.63.2.020501.

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Vernanda, Yustinus, Seng Hansun, and Marcel Bonar Kristanda. "Indonesian language email spam detection using N-gram and Naïve Bayes algorithm." Bulletin of Electrical Engineering and Informatics 9, no. 5 (2020): 2012–19. http://dx.doi.org/10.11591/eei.v9i5.2444.

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Indonesia is ranked the top 8th out of the total country population in the world for the global spammers. Web-based spam filter service with the REST API type can be used to detect email spam in the Indonesian language on the email server or various types of email server applications. With REST API, then there will be data exchange between the applications with JSON data type using existing HTTP commands. One type of spam filter commonly used is Bayesian Filtering, where the Naïve Bayes algorithm is used as a classification algorithm. Meanwhile, the N-gram method is used to increase the accura

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Yustinus, Vernanda, Hansun Seng, and Bonar Kristanda Marcel. "Indonesian language email spam detection using N-gram and Naïve Bayes algorithm." Bulletin of Electrical Engineering and Informatics 9, no. 5 (2020): 2012–19. https://doi.org/10.11591/eei.v9i5.2444.

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Indonesia is ranked the top 8th out of the total country population in the world for the global spammers. Web-based spam filter service with the REST API type can be used to detect email spam in the Indonesian language on the email server or various types of email server applications. With REST API, then there will be data exchange between the applications with JSON data type using existing HTTP commands. One type of spam filter commonly used is Bayesian Filtering, where the Naïve Bayes algorithm is used as a  classification algorithm. Meanwhile, the N-gram method is used to increase

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Zhu, Chengguang, Zhongpai Gao, Jiankang Zhao, Haihui Long, and Chuanqi Liu. "Weighted total least squares–Bayes filter-based estimation of relative pose for a space non-cooperative unknown target without a priori knowledge." Measurement Science and Technology 33, no. 2 (2021): 025004. http://dx.doi.org/10.1088/1361-6501/ac3624.

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Abstract The estimation of relative pose of a space non-cooperative target is an attractive yet challenging task due to the complexity of the target background and illumination, and the lack of a priori knowledge. Unfortunately, these negative factors have a grave impact on the accuracy of the estimation and the robustness of the filter algorithms. In response, this paper proposes a novel filter algorithm for estimating relative pose to improve robustness based on a stereovision system. First, to obtain a coarse relative pose, the weighted total least squares (WTLS) algorithm is adopted to est

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Palvi, Sethi*1 &. Dr. Vishal Pareek2. "RESTORATION OF DEGRADED IMAGES USING HYBRID DENOISED MODEL WITH FUSION AND ENHANCEMENT." GLOBAL JOURNAL OF ADVANCED ENGINEERING TECHNOLOGIES AND SCIENCES 6, no. 7 (2019): 31–39. https://doi.org/10.5281/zenodo.3357868.

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Image reclamation is a craftsmanship to improve the idea of Image by means of assessing the proportion of commotions and obscure occupied with the Image. Despite the vital research drove on this subject, the improvement of capable denoising procedures is up 'til now a persuading test. The huge inadequacy is that while redesign, the splendor of the Image self-destructs in an impressive sum. The Image fusions techniques perform well spatially however more often than not present otherworldly bending. Which implies that the variety of tint when the combination procedure has showed up? There is

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