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Decision templates for multiple classifier fusion: an experimental comparison

Ludmila I. Kuncheva, James C. Bezdek, Robert P.W. Duin
2001 Pattern Recognition  
Multiple classifier fusion may generate more accurate classification than each of the constituent classifiers. Fusion is often based on fixed combination rules like the product and average.  ...  We present here a simple rule for adapting the class combiner to the application. c decision templates (one per class) are estimated with the same training set that is used for the set of classifiers.  ...  Fusion techniques used for comparison Techniques for crisp individual labels C1: Majority vote.  ... 
doi:10.1016/s0031-3203(99)00223-x fatcat:ra66kywynfdyfbjpwrwjgltpiu

Combining Fingerprint and Voiceprint Biometrics for Identity Verification: an Experimental Comparison [chapter]

Yuan Wang, Yunhong Wang, Tieniu Tan
2004 Lecture Notes in Computer Science  
Combining multiple biometrics may enhance the performance of personal authentication system in accuracy and reliability.  ...  The experimental results show that Support Vector Machine and the Dempster-Shafer method are superior to other schemes.  ...  Conclusion Fusion of multiple biometrics has recently gained more interests with an increasing emphasis on security.  ... 
doi:10.1007/978-3-540-25948-0_90 fatcat:vezpo4dqynhrla5vksvdrzjkxq

An Experimental Comparison of Different Methods for Combining Biometric Identification Systems [chapter]

Emanuela Marasco, Carlo Sansone
2011 Lecture Notes in Computer Science  
In this paper, we experimentally compare the behavior of different rules for integrating different biometric identification systems.  ...  We considered trained and fixed fusion methods at score, rank and decision level.  ...  Fusion Approaches at Score-Level Fusion at match score level concerns combining the match scores generated by multiple classifiers in order to make a decision about the identity of the subject.  ... 
doi:10.1007/978-3-642-24088-1_27 fatcat:7tkuqwtrezar7nisabyo6tamoi

Information fusion in biometrics

Arun Ross, Anil Jain
2003 Pattern Recognition Letters  
However, an effective fusion scheme is necessary to combine the information presented by multiple domain experts.  ...  Further, multibiometric systems provide anti-spoofing measures by making it difficult for an intruder to spoof multiple biometric traits simultaneously.  ...  Multiple biometric fusion Multibiometric fusion refers to the fusion of multiple biometric indicators.  ... 
doi:10.1016/s0167-8655(03)00079-5 fatcat:2g3yqzec7zgjvlxnw5stk73hme

Information Fusion in Biometrics [chapter]

Arun Ross, Anil K. Jain, Jian-Zhong Qian
2001 Lecture Notes in Computer Science  
However, an effective fusion scheme is necessary to combine the information presented by multiple domain experts.  ...  Further, multibiometric systems provide anti-spoofing measures by making it difficult for an intruder to spoof multiple biometric traits simultaneously.  ...  Multiple biometric fusion Multibiometric fusion refers to the fusion of multiple biometric indicators.  ... 
doi:10.1007/3-540-45344-x_52 fatcat:vrux6ntqvbhlbakkasfesxysr4

Decision Fusion for Face Authentication [chapter]

Jacek Czyz, Mohammad Sadeghi, Josef Kittler, Luc Vandendorpe
2004 Lecture Notes in Computer Science  
In this paper we study two aspects of decision fusion for enhancing face authentication.  ...  First, sequential fusion of scores obtained on successive video frames of a user's face is used to reduce the error rate.  ...  A performance comparison between this approach and the sequential fusion presented in this paper could be an interesting future study.  ... 
doi:10.1007/978-3-540-25948-0_93 fatcat:iccf54y32rfmhlt3qgml44rbfy

Designing classifier fusion systems by genetic algorithms

L.C. Jain, L.I. Kuncheva
2000 IEEE Transactions on Evolutionary Computation  
We suggest two simple ways to use a genetic algorithm (GA) to design a multiple-classifier system.  ...  The multiple-classifier systems designed with the two GAs were compared against classifiers using: 1) all features; 2) the best feature subset found by the sequential backward selection (SBS) method; and  ...  Architecture of the decision templates classifier fusion scheme.  ... 
doi:10.1109/4235.887233 fatcat:lxdtxjip55hezavzcwqd754xoi

A Multiple Classifier Fusion Algorithm Using Weighted Decision Templates

Aizhong Mi, Lei Wang, Junyan Qi
2016 Scientific Programming  
From fully considering the classifier performance differences and the training sample information, a multiple classifier fusion algorithm using weighted decision templates is proposed in this paper.  ...  An experimental comparison was performed on 15 data sets from the KDD'99, UCI, and ELENA databases. The experimental results indicate that the algorithm can achieve better classification performance.  ...  Therefore, the study of multiple classifier fusion is still an open problem.  ... 
doi:10.1155/2016/3943859 fatcat:v6dcnhjtpfag7ahelggmb5co64

Comparing early and late data fusion methods for gene expression prediction

Matteo Re
2010 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
promoter regions is an oversimplification as pointed out by recent findings demonstrating the existence of many regulatory levels involved in the fine modulation of gene transcription levels.  ...  Even if encouraging results were obtained in gene expression patterns prediction experiments the assumption that all the signals required for the regulation of gene expression are contained in the gene  ...  The author would also like to expressly thank Giorgio Valentini for the examination of early versions of the manuscript.  ... 
doi:10.1007/s00500-010-0599-6 fatcat:7egzfl2vovfdvb3vf43vj23aga

A decision fusion method based on multiple support vector machine system for fusion of hyperspectral and LIDAR data

Behnaz Bigdeli, Farhad Samadzadegan, Peter Reinartz
2014 International Journal of Image and Data Fusion  
Fusion of remote sensing data from multiple sensors has been remarkably increased for classification.  ...  The proposed method applied a support vector machine (SVM)-based classifier fusion system for fusion of hyperspectral and LIDAR data in the decision level.  ...  sets used in this study and the IEEE GRSS Data Fusion Technical Committee for organising the 2013 Data Fusion Contest.  ... 
doi:10.1080/19479832.2014.919964 fatcat:fac6nxytmbbudgm4ambiwyb4ai

Using Data Fusion For Biometric Verification

Richard A. Wasniowski
2007 Zenodo  
Strategies for feature extraction and sensor fusion are considered and contrasted. Issues related to performance assessment, deployment and standardization are discussed.  ...  A wide spectrum of systems require reliable personal recognition schemes to either confirm or determine the identity of an individual person.  ...  Specific features are extracted from the biometric samples to form templates for future comparisons. b) The templates thus obtained are stored for future comparison.  ... 
doi:10.5281/zenodo.1058001 fatcat:5dps4rrfu5ainnvgy32ep22ydm

Ethnicity classification based on gait using multi-view fusion

De Zhang, Yunhong Wang, Bir Bhanu
2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops  
Feature fusion, score fusion and decision fusion from multiple views of gait are explored.  ...  The classification rate is improved by fusing multiple camera views and a comparison among different fusion schemes shows that the MPCA based feature fusion performs the best.  ...  Figure 2 . 2 The basic frames of the fusion schemes used in this paper for comparison: (a) fusion at feature level, (b) fusion at score level, (c) fusion at decision level.  ... 
doi:10.1109/cvprw.2010.5544614 dblp:conf/cvpr/ZhangWB10 fatcat:aq24tkdcrfezpdnyzhnrxb5e64

Multi-algorithm fusion with template protection

E.J.C. Kelkboom, X. Zhou, J. Breebaart, R.N.J. Veldhuis, C. Busch
2009 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems  
In this work we analyze fusion of the protected template from two 3D recognition algorithms (multi-algorithm fusion) at feature-, score-, and decision-level.  ...  We experimentally determine the performance of different fusion methods at each level.  ...  The comparison within the Fusion Classifier module can occur at different levels, namely at feature-, score-, or decision-level.  ... 
doi:10.1109/btas.2009.5339045 fatcat:jodvaigmkbcadobl2javukcta4

Fusion in Multimodal Biometric System: A Review

G. Kaur, S. Bhushan, D. Singh
2017 Indian Journal of Science and Technology  
Score level, feature level, rank level and decision fusion is followed by feature optimization using methods such as genetic algorithms and artificial neural networks.  ...  These methods vary in efficiency and are highly dependant upon the selection of type of biometric chosen for fusion.  ...  Proposed algorithm iteratively generates ranks for each partition of the user template. Finally, ranks from template partitions were fused to evaluate the fusion rank for the classification.  ... 
doi:10.17485/ijst/2017/v10i19/114382 fatcat:tern7losm5gfhaw6jjmw54r4mm

Fusion of Iris Segmentation Results [chapter]

Andreas Uhl, Peter Wild
2013 Lecture Notes in Computer Science  
This paper introduces the concept of multi-segmentation fusion for combining independent iris segmentation results.  ...  Fusion at segmentation level is useful to (1) obtain more robust recognition rates compared to single segmentation; (2) avoid additional storage requirements compared to feature-level fusion, and (3) save  ...  sample) or verification mode (1-to-1 comparison to justify the authenticity of an identification claim as genuine or imposter ), this fusion type consolidates the outcome of individual decision processes  ... 
doi:10.1007/978-3-642-41827-3_39 fatcat:c567ytg56ng3hpvm46f5d7ti6u
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