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Dynamic Bayesian Combination of Multiple Imperfect Classifiers
[article]
2012
arXiv
pre-print
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Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. ...
Finally we present a dynamic Bayesian classifier combination approach and investigate the changes in base classifier performance over time. ...
Discussion In this paper we present a very computationally efficient, variational Bayesian, approach to imperfect multiple classifier combination. ...
arXiv:1206.1831v1
fatcat:izkywacgozcofegcrbpmj5djyq
Dynamic Bayesian Combination of Multiple Imperfect Classifiers
[chapter]
2013
Studies in Computational Intelligence
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Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. ...
Finally we present a dynamic Bayesian classifier combination approach and investigate the changes in base classifier performance over time. ...
Discussion In this paper we present a very computationally efficient, variational Bayesian, approach to imperfect multiple classifier combination. ...
doi:10.1007/978-3-642-36406-8_1
fatcat:qw4eavqggvbu3ouikiamcs6ooi
Dynamically weighted ensemble classification for non-stationary EEG processing
2013
Journal of Neural Engineering
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The decisions from these multiple classifiers are dynamically combined based on the distances of the cluster centres to each test data sample being classified. ...
This paper proposes a novel Dynamically Weighted Ensemble Classification (DWEC) framework to address the non-stationarity. An ensemble of multiple classifiers are trained on clustered features. ...
Recent advances include a unifying framework for learning linear combiners for classifier ensembles [15] and Bayesian combination of multiple imperfect classifiers proposed by Simpson et al in [16] ...
doi:10.1088/1741-2560/10/3/036007
pmid:23574821
fatcat:mrygve3tcjdf3n5qf3i436zvea
Game Theory for Network Security
2013
IEEE Communications Surveys and Tutorials
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of subcategories. ...
In addition to the introduction to the state of the art, we discuss the limitations of those game theoretic approaches and propose future research directions. ...
The dynamic Bayesian game in [18] includes multiple stages, and each of the stages is a static game. ...
doi:10.1109/surv.2012.062612.00056
fatcat:wn7l3y2sgvaqvaneotfzhaxzoy
Novel classifier fusion approahces for fault diagnosis in automotive systems
2007
IEEE Autotestcon Proceedings
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Specifically, we develop three novel classifier fusion approaches: class-specific Bayesian fusion, joint optimization of fusion center and of individual classifiers, and dynamic fusion. ...
The results demonstrate that dynamic fusion and joint optimization, and class-specific Bayesian fusion outperform traditional fusion approaches. ...
ACKNOWLEDGEMENT This work was supported by Toyota Technical Center at the University of Connecticut under agreement AG030699-02. ...
doi:10.1109/autest.2007.4374227
fatcat:46lc32pujneg5nlakgk7ugnr54
Multibiometric Systems: Overview, Case Studies, and Open Issues
[chapter]
2009
Advances in Pattern Recognition
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Multibiometric systems combine the information presented by multiple biometric sensors, algorithms, samples, units, or traits in order to establish the identity of an individual. ...
Information fusion refers to the reconciliation of evidence presented by multiple sources of information in order to generate a decision. ...
[30] (logistic regression classifier) and [45] (Bayesian classifier). ...
doi:10.1007/978-1-84882-385-3_11
fatcat:xipdozpwjbhzvexgftr2cdtfrq
Dynamic fusion of classifiers for fault diagnosis
2007
2007 IEEE International Conference on Systems, Man and Cybernetics
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Here, we discuss dynamic fusion of classifiers which is a special case of the dynamic multiple fault diagnosis (DMFD) problem [1]-[3]. ...
The results demonstrate that an ensemble of classifiers, when fused over time, reduces the diagnostic error as compared to a single classifier and static fusion of classifiers trained over the entire batch ...
The true states of classifiers are also hidden because the classifiers are imperfect. ...
doi:10.1109/icsmc.2007.4414167
dblp:conf/smc/SinghCKPNCPQ07
fatcat:kivld7nhfnex3pkaoy7wdhgmr4
Feature Tracking and Expression Recognition of Face Using Dynamic Bayesian Network
English
2014
International Journal of Engineering Trends and Technoloy
English
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In proposed system, in contrast to the mainstream approaches, we are trying to build a probabilistic model based on the Dynamic Bayesian Network (DBN) to capture the facial interactions at different levels ...
Due to the difficulty of obtaining controlled video sequences of standard facial expressions, many psychological and neurophysiologic studies of facial expression processing have used single image motivations ...
Given the proposed model, all three levels of facial activities are recovered simultaneously through a probabilistic inference by systematically combining the measurements from multiple sources at different ...
doi:10.14445/22315381/ijett-v8p293
fatcat:jnt2mhufsrfnllw7b6dkzwx63u
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence: Navigating the absence of a gold standard
2021
PLoS ONE
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Given the dynamic nature of this pandemic, Bayesian Latent Class Models can be used to correct for imperfect test characteristics and waning IgG antibody signals. ...
Seroprevalence rates were compared using multiple composite reference standards and by a series of Bayesian Latent Class Models. ...
In contrast to CRS which classifies individuals as either positive or negative, BLCA uses a likelihood-based approach from multiple imperfect assays to estimate test characteristics and prevalence. ...
doi:10.1371/journal.pone.0257743
pmid:34555095
fatcat:ucd6rcqj3banrhgru4ayepuoae
Object Recognition and Identification Using ESM Data
[article]
2016
arXiv
pre-print
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In typical surveillance systems multiple ESM sensors are usually deployed along with kinematic sensors like radar. ...
Recognition and identification of unknown targets is a crucial task in surveillance and security systems. ...
Imperfect nature of information can also be considered in the architecture. ...
arXiv:1607.01355v1
fatcat:rvznjlospvegvfwy5bdoynzzri
Multi-Sensor Data and Knowledge Fusion – A Proposal for a Terminology Definition
[article]
2020
arXiv
pre-print
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The focus in the first part of the paper at hand is on the clear definition of the terminology and the development of an appropriate ontology of the fusion components and the fusion level. ...
However, a clear definition of the type of fusion is not always provided due to inconsistent literature. ...
Decision Fusion The decision fusion of multiple classifiers may consist of the direct combination of decisions or the selection of one suitable classifier for a specific input area. ...
arXiv:2001.04171v1
fatcat:2wj5xe3bqrdf3bt7sn2em7vqne
Novel Classifier Fusion Approaches for Fault Diagnosis in Automotive Systems
2009
IEEE Transactions on Instrumentation and Measurement
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Specifically, we develop three novel classifier fusion approaches: class-specific Bayesian fusion, joint optimization of fusion center and of individual classifiers, and dynamic fusion. ...
In this paper, we consider the problem of fusing classifier decisions to reduce diagnostic errors. ...
The objective of classifier fusion is to reduce the diagnostic errors by combining the results of individual classifiers. ...
doi:10.1109/tim.2008.2004340
fatcat:qebotwkravc35bfs4fpgdnvy6a
A Survey of Game Theory as Applied to Network Security
2010
2010 43rd Hawaii International Conference on System Sciences
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This paper surveys the existing game theoretic solutions which are designed to enhance network security and presents a taxonomy for classifying the proposed solutions. ...
This taxonomy should provide the reader with a better understanding of game theoretic solutions to a variety of cyber security problems. ...
Dynamic games A dynamic game can be either of complete or incomplete information. Moreover, a dynamic game may involve perfect or imperfect information. ...
doi:10.1109/hicss.2010.35
dblp:conf/hicss/RoyESDSW10
fatcat:hom3hguma5a4nji65wdcoiseoq
Abstracts of Recent PhDs
2008
Knowledge engineering review (Print)
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'environment' and a number of strategic tradeoffs. ...
The variety of different auction rules, the restrictions in supply or demand, and the agents' combinatorial preferences for the different commodities, have led to the creation of a very complex multi-agent ...
Furthermore, we present several novel Bayes-Nash equilibria for m th price multi-unit auctions with multiple possible closing times, one of which is chosen randomly, and therefore multiple rounds of bidding ...
doi:10.1017/s0269888908001331
fatcat:lil6wn52szbdjklbdqa3m4durq
Comparison of levels and fusion approaches for multimodal biometrics
2021
Indonesian Journal of Electrical Engineering and Computer Science
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In this paper we have discussed comprehensive representation on the system of multimodal biometric, various modes of undertakings, the significance of information fusion, a different section is allotted ...
In today's world, most of the systems are unimodal biometrics having a lot of limitations to overcome those multimodal biometrics comes in to picture. ...
Bayesian inference and dynamic Bayesian network come under generative, whereas neural networks and supportive vector machines are under Discriminative models. ...
doi:10.11591/ijeecs.v23.i2.pp791-801
fatcat:j64gws32kzfufa3kg2dfhpxjwi
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