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Evaluating Score Normalization Methods in Data Fusion [chapter]

Shengli Wu, Fabio Crestani, Yaxin Bi
2006 Lecture Notes in Computer Science  
In data fusion, score normalization is a step to make scores, which are obtained from different component systems for all documents, comparable to each other.  ...  In this paper, we evaluate four linear score normalization methods, namely the fitting method, Zero-one, Sum, and ZMUV, through extensive experiments.  ...  Conclusion In this paper, we have evaluated four linear score normalization methods, namely the fitting method, Zero-one, Sum and ZMUV.  ... 
doi:10.1007/11880592_57 fatcat:saan5vztofd6ppl2x63x5etm7u

DCU Linking Runs at MediaEval 2012 Search and Hyperlinking Task

Shu Chen, Gareth J. F. Jones, Noel E. O'Connor
2012 MediaEval Benchmarking Initiative for Multimedia Evaluation  
Two categories of fusion strategy, score-based and rank-based methods, were used to combine scores from different modalities to produce potential inter-item links.  ...  We describe Dublin City University (DCU)'s participation in the Hyperlinking sub-task of the MediaEval 2012 Search and Hyperlinking Task.  ...  A number of methods are evaluated in [8] and [7] , which provide detailed guidelines underpinning the design of our data fusion strategy.  ... 
dblp:conf/mediaeval/ChenJO12 fatcat:gn2nagi4x5dsjlihxc6i7cemfy

On the Performance Prediction and Validation for Multisensor Fusion

Rong Wang, Bir Bhanu
2007 2007 IEEE Conference on Computer Vision and Pattern Recognition  
Finally, using this representation, we derive a set of metrics to evaluate the sensor fusion performance and find the optimal sensor combination.  ...  In this paper, we present a theoretical approach that predicts the performance of sensor fusion that allows us to select the optimal combination.  ...  As the fusion system evaluation and prediction in the XM2VTS database, we apply the Min-Max, Z-score, and Tanh normalization methods to normalize these four baseline systems.  ... 
doi:10.1109/cvpr.2007.383112 dblp:conf/cvpr/WangB07 fatcat:biqagcowzrhnriccw46xvdm2ny

An Evaluation of Score Level Fusion Approaches for Fingerprint and Finger-vein Biometrics [article]

Kamer Vishi, Vasileios Mavroeidis
2018 arXiv   pre-print
In this paper, we evaluate combinations of score normalization and fusion techniques using two modalities (fingerprint and finger-vein) with the goal of identifying which one achieves better improvement  ...  The individual scores obtained from finger-veins and fingerprints are combined at score level using three score normalization techniques (min-max, z-score, hyperbolic tangent) and four score fusion approaches  ...  The most used score normalization techniques that are also used and evaluated in this paper are Min-Max (MM), Z-Score (ZS), and Hyperbolic Tangent (TanH). These methods are discussed below.  ... 
arXiv:1805.10666v1 fatcat:cfd7aemaqfgcxnd5hofbrsckaa

Multimodal biometrics

Robert Snelick, Mike Indovina, James Yen, Alan Mink
2003 Proceedings of the 5th international conference on Multimodal interfaces - ICMI '03  
A key aspect of our approach is to leverage confidence level scores from preexisting single-mode data.  ...  An example presents a multimodal biometrics system analysis that explores various normalization and fusion techniques for face and fingerprint classifiers.  ...  Normalization Normalization, step 6 of our testing methodology, is recommended for certain data fusion methods.  ... 
doi:10.1145/958444.958447 fatcat:oqbsebpnxzg65e5aubtvzhheva

Multimodal biometrics

Robert Snelick, Mike Indovina, James Yen, Alan Mink
2003 Proceedings of the 5th international conference on Multimodal interfaces - ICMI '03  
A key aspect of our approach is to leverage confidence level scores from preexisting single-mode data.  ...  An example presents a multimodal biometrics system analysis that explores various normalization and fusion techniques for face and fingerprint classifiers.  ...  Normalization Normalization, step 6 of our testing methodology, is recommended for certain data fusion methods.  ... 
doi:10.1145/958432.958447 dblp:conf/icmi/SnelickIYM03 fatcat:onsau27qu5acho7mikdxnauxm4

An Evaluation Survey of Score Normalization in Multibiometric Systems

Yong Li, Jian Ping Yin, En Zhu
2011 Advanced Engineering Forum  
PL and FF normalization outperform other methods in many applications.  ...  Multibiometric fusion is an active research area for many years. Score normalization is to transform the scores from different matchers to a common domain.  ...  Table 2 shows the EER of multi-modal fusion among the 7 normalization methods. In order to evaluate the performance precisely, for each fusion, we give each matcher the performance mark.  ... 
doi:10.4028/www.scientific.net/aef.1.168 fatcat:sqt655udsbcadgv2p63lqd2ycy

SUT System Description for NIST SRE 2016 [article]

Hossein Zeinali, Hossein Sameti, Nooshin Maghsoodi
2017 arXiv   pre-print
Then, we describe the classifier and score normalization methods. And finally, some results on SRE16 evaluation dataset are reported and analyzed.  ...  UBM and i-vector extractor training are the next details in this paper. As one of the important steps in system preparation, preconditioning the i-vectors are explained in more details.  ...  Score normalization For score normalization, a specific version of s-norm method was used.  ... 
arXiv:1706.05077v1 fatcat:4t4vusayx5gsvdaeiuxamwkloa

Learning Non-linear Calibration for Score Fusion with Applications to Image and Video Classification

Tianyang Ma, Sangmin Oh, Amitha Perera, Longin Jan Latecki
2013 2013 IEEE International Conference on Computer Vision Workshops  
Our approach provides a unified approach to jointly solve score normalization and fusion classifier learning.  ...  In this work, we propose a robust score fusion approach which learns non-linear score calibrations for multiple base classifier scores.  ...  In addition, we also evaluate the robustness of the fusion methods in Sec. 4.1.1. In particular, we evaluate their performance under changes in the distribution of base classifier scores.  ... 
doi:10.1109/iccvw.2013.50 dblp:conf/iccvw/MaOPL13 fatcat:p3m3r7k2tvh6rn33lqf3ecu6dq

Fusion fault localizers

Lucia, David Lo, Xin Xia
2014 Proceedings of the 29th ACM/IEEE international conference on Automated software engineering - ASE '14  
We investigate two score normalization methods, two technique selection methods, and five data fusion methods resulting in twenty variants of Fusion Localizer.  ...  Our proposed approach consists of three steps: score normalization, technique selection, and data fusion.  ...  Le for his help in collecting the real bugs and test suites from Lucene and Ant bug tracking and version control systems following the approach by Dallmeier and Zimmermann [8] .  ... 
doi:10.1145/2642937.2642983 dblp:conf/kbse/LuciaLX14 fatcat:q7eyixfjfbg6jbdnxn3czdam64

DEMIR at ImageCLEFMed 2011: Evaluation of Fusion Techniques for Multimodal Content-based Medical Image Retrieval

Adil Alpkocak, Okan Ozturkmenoglu, Tolga Berber, Ali Hosseinzadeh Vahid, Roghaiyeh Gachpaz Hamed
2011 Conference and Labs of the Evaluation Forum  
This year, we evaluated fusion and re-ranking method which is based on the best low level feature of images with best text retrieval result.  ...  We improved results by examination of different weighting models for retrieved text data and low level features.  ...  Moreover results of weighted average combination method are better than normal average method in all approach.  ... 
dblp:conf/clef/AlpkocakOBVH11 fatcat:y2ny27frjfbqrlphupraahd6ja

Audio signal detection and enhancement based on linear CMOS array and multi-channel data fusion

Cong Dai, Chang Liu, Yanfang Wu, Xiaozhong Wang, Hongyan Fu, Haixin Sun
2020 IEEE Access  
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.  ...  The SegSNR evaluating results of the nw_ds and phat_ds fusion algorithms are shown in Fig. 6(b) and Fig. 6 (c) respectively. Direct ds fusion only obtains about 1.0 dB increase in SegSNR score.  ...  The higher the score, the better is the audio signal, which reflects the quality of the fusion method.  ... 
doi:10.1109/access.2020.3010325 fatcat:aayv255aoreu3aujul3dybyq5a

A novel hybrid score level and decision level fusion scheme for cancelable multi-biometric verification

Rudresh Dwivedi, Somnath Dey
2018 Applied intelligence (Boston)  
The rigorous experimental evaluations on three virtual databases indicate that the proposed hybrid fusion framework outperforms over the component level or individual fusion methods (score level and decision  ...  mitigate the limitations in the individual score or decision fusion mechanisms.  ...  In this work, normalization is not required since the methods utilized in score computation generate the scores in the interval of [0,1].  ... 
doi:10.1007/s10489-018-1311-2 fatcat:j55q7rrmszcvpmdv2iawxo7xv4

A Technique of Data Fusion for Effective Text Retrieval

Manjusha Sanke
2015 International Journal of Computer Applications  
This paper focuses on Norm_CombMNZ algorithm which normalizes the result obtained from CombMNZ, so that scores lie in 0 to 1 common range and better ranking judgment can be made.  ...  CombMNZ is a score-based fusion algorithm which adds all the reported scores for a document and multiplies the sum value to the number of retrieval models that have returned that document.  ...  Several data fusion methods [1] are developed which are classified based on whether they rely on rank or score, or whether they require training data or not.  ... 
doi:10.5120/19556-1303 fatcat:4hzs2ahcyjdwbc5wey6r3kodk4

A Model based Approach for Multimodal Biometric Recognition

Manas KumarChoudhury, Y.Srinivas Y.Srinivas
2014 International Journal of Computer Applications  
In this approach the concepts of fusion together with Generalized Gamma Distribution (GGD) are utilized.  ...  The performance of the model is evaluated using synthetic data and evaluation is carried out by considering metrics like False Acceptance Rate (FAR), and False Rejection Rate (FRR).  ...  These features are fused using a score level fusion. SCORE LEVEL FUSION In order to map the features from the multiple traits, score level fusion is used.  ... 
doi:10.5120/18250-9338 fatcat:ot7mkwerwzbtljg3sd2wu4ez64
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