Relevant bibliographies by topics / Data fusion algorithms

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Data fusion algorithms'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Data fusion algorithms.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Data fusion algorithms"

1

ZHU, SHANFENG, QIZHI FANG, and WEIMIN ZHENG. "SOCIAL CHOICE FOR DATA FUSION." International Journal of Information Technology & Decision Making 03, no. 04 (December 2004): 619–31. http://dx.doi.org/10.1142/s0219622004001288.

Full text
Abstract:
Social choice theory is the study of decision theory on how to aggregate separate preferences into group's rational preference. It has wide applications, especially on the design of voting rules, and brings far-reaching influence on the development of modern political science and welfare economics. With the advent of the information age, social choice theory finds its up-to-date application on designing effective Metasearch engines. Metasearch engines provide effective searching by combining the results of multiple source search engines that make use of diverse models and techniques. In this work, we analyze social choice algorithms in a graph-theoretic approach. In addition to classical social choice algorithms, such as Borda and Condorcet, we study one special type of social choice algorithms, elimination voting, to tackle Metasearch problem. Some new algorithms are proposed and examined in the fusion experiment on TREC data. It shows that these elimination voting algorithms achieve satisfied performance when compared with Borda algorithm.
APA, Harvard, Vancouver, ISO, and other styles
2

Quadri, S. A., and Othman Sidek. "Role of Algorithm Engineering in Data Fusion Algorithms." Journal of Computational Intelligence and Electronic Systems 2, no. 1 (June 1, 2013): 29–35. http://dx.doi.org/10.1166/jcies.2013.1046.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

LIPOVETSKY, STAN. "DATA FUSION IN SEVERAL ALGORITHMS." Advances in Adaptive Data Analysis 05, no. 03 (July 2013): 1350014. http://dx.doi.org/10.1142/s1793536913500143.

Full text
Abstract:
Data fusion consists of the process of integrating several datasets with some common variables, and other variables available only in partial datasets. The main problem of data fusion can be described as follows. From one source, having X0 and Y0 datasets (with N0 observations by multiple x and y variables, n and m of those, respectively), and from another source, having X1 data (with N1 observations by the same nx-variables), we need to estimate the missing portion of the Y1 data (of size N1 by m variables) in order to combine all the data into one set. Several algorithms are considered in this work, including estimation of weights proportional to the distances from each ith observation in the X1 "recipients" dataset to all observations in the X0 "donors" dataset. Or we can use a sample balancing technique with the maximum effective base performed by applying ridge-regression for the Gifi system of binaries obtained from the x-variables for the best fit of the "donors" X0 data to the margins defined by each respondent in the "recipients" X1 dataset. Then the weighted regressions of each y in the Y0 dataset by all variables in the X0 are constructed. For each ith observation in the dataset X0, these regressions are used for predicting the y-variables in the Y1 "recipients" dataset. If X and Y are the same n variables from different sources, the dual partial least squares technique and a special regression model with dummies defining each of the three available sets are used for prediction of the Y1 data.
APA, Harvard, Vancouver, ISO, and other styles
4

Zhang, Jie. "Security Technology of Wireless Sensor Internet of Things Based on Data Fusion." International Journal of Online Engineering (iJOE) 13, no. 11 (November 22, 2017): 25. http://dx.doi.org/10.3991/ijoe.v13i11.7748.

Full text
Abstract:
<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">In order to prove the effect of data fusion technology in the Internet of things, a wireless sensor Internet of things security technology based on data fusion is designed, and the impact of data fusion in the field of communication technology is studied. Therefore, two security fusion algorithms are designed on the basis of analyzing and comparing the advantages and disadvantages of various security fusion algorithms, namely, data security fusion algorithm EDCSDA and approximate fusion algorithm PADSA. By analyzing the probability distribution model of the data collected by the nodes, the disturbance data is superimposed on the original data to hide the effect of the original data. A test bed system for perception layer of the Internet of things is designed and implemented. The test results prove the feasibility of the two algorithms. Meanwhile, it shows that the two algorithms can reduce the transmission overhead of the network while guaranteeing the security. Based on the above finding, it is concluded that data fusion technology is very effective for improving network efficiency and prolonging the network life cycle as one of the key technologies in the perception layer of Internet of things.</span>
APA, Harvard, Vancouver, ISO, and other styles
5

Tan, Yuxiang, Yann Tambouret, and Stefano Monti. "SimFuse: A Novel Fusion Simulator for RNA Sequencing (RNA-Seq) Data." BioMed Research International 2015 (2015): 1–5. http://dx.doi.org/10.1155/2015/780519.

Full text
Abstract:
The performance evaluation of fusion detection algorithms from high-throughput sequencing data crucially relies on the availability of data with known positive and negative cases of gene rearrangements. The use of simulated data circumvents some shortcomings of real data by generation of an unlimited number of true and false positive events, and the consequent robust estimation of accuracy measures, such as precision and recall. Although a few simulated fusion datasets from RNA Sequencing (RNA-Seq) are available, they are of limited sample size. This makes it difficult to systematically evaluate the performance of RNA-Seq based fusion-detection algorithms. Here, we present SimFuse to address this problem. SimFuse utilizes real sequencing data as the fusions’ background to closely approximate the distribution of reads from a real sequencing library and uses a reference genome as the template from which to simulate fusions’ supporting reads. To assess the supporting read-specific performance, SimFuse generates multiple datasets with various numbers of fusion supporting reads. Compared to an extant simulated dataset, SimFuse gives users control over the supporting read features and the sample size of the simulated library, based on which the performance metrics needed for the validation and comparison of alternative fusion-detection algorithms can be rigorously estimated.
APA, Harvard, Vancouver, ISO, and other styles
6

Castanedo, Federico. "A Review of Data Fusion Techniques." Scientific World Journal 2013 (2013): 1–19. http://dx.doi.org/10.1155/2013/704504.

Full text
Abstract:
The integration of data and knowledge from several sources is known as data fusion. This paper summarizes the state of the data fusion field and describes the most relevant studies. We first enumerate and explain different classification schemes for data fusion. Then, the most common algorithms are reviewed. These methods and algorithms are presented using three different categories: (i) data association, (ii) state estimation, and (iii) decision fusion.
APA, Harvard, Vancouver, ISO, and other styles
7

Abdulhafiz, Waleed A., and Alaa Khamis. "Handling Data Uncertainty and Inconsistency Using Multisensor Data Fusion." Advances in Artificial Intelligence 2013 (November 3, 2013): 1–11. http://dx.doi.org/10.1155/2013/241260.

Full text
Abstract:
Data provided by sensors is always subjected to some level of uncertainty and inconsistency. Multisensor data fusion algorithms reduce the uncertainty by combining data from several sources. However, if these several sources provide inconsistent data, catastrophic fusion may occur where the performance of multisensor data fusion is significantly lower than the performance of each of the individual sensor. This paper presents an approach to multisensor data fusion in order to decrease data uncertainty with ability to identify and handle inconsistency. The proposed approach relies on combining a modified Bayesian fusion algorithm with Kalman filtering. Three different approaches, namely, prefiltering, postfiltering and pre-postfiltering are described based on how filtering is applied to the sensor data, to the fused data or both. A case study to find the position of a mobile robot by estimating its x and y coordinates using four sensors is presented. The simulations show that combining fusion with filtering helps in handling the problem of uncertainty and inconsistency of the data.
APA, Harvard, Vancouver, ISO, and other styles
8

Gan, Hock, Iosif Mporas, Saeid Safavi, and Reza Sotudeh. "Speaker Identification Using Data-Driven Score Classification." Image Processing & Communications 21, no. 2 (June 1, 2016): 55–63. http://dx.doi.org/10.1515/ipc-2016-0011.

Full text
Abstract:
Abstract We present a comparative evaluation of different classification algorithms for a fusion engine that is used in a speaker identity selection task. The fusion engine combines the scores from a number of classifiers, which uses the GMM-UBM approach to match speaker identity. The performances of the evaluated classification algorithms were examined in both the text-dependent and text-independent operation modes. The experimental results indicated a significant improvement in terms of speaker identification accuracy, which was approximately 7% and 14.5% for the text-dependent and the text-independent scenarios, respectively. We suggest the use of fusion with a discriminative algorithm such as a Support Vector Machine in a real-world speaker identification application where the text-independent scenario predominates based on the findings.
APA, Harvard, Vancouver, ISO, and other styles
9

Yin, Hu, Yun Fei Lv, and Wei Wei Wang. "Reacher in Users Recommended of Social Data." Applied Mechanics and Materials 303-306 (February 2013): 2416–24. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.2416.

Full text
Abstract:
We discuss some key techniques associated with integrating user social data recommendation into entity search engine, which can provide entity search engine more accurate information and make up for automatically fetching information on Web. The goal of social data recommendation is to make search engine become a content provider, and solve some challenges that traditional architecture of search engine has faced with, such as limited resources, accurate search, etc. To this end, we describe the storage format of the user social recommended data and submission methods for them. For the purpose of fusing this structural information into entity search engine, we present formal definitions related to Web entity fusion, and give several important fusion operators, and discuss their properties. Finally, we propose a Web entity fusion algorithm, which exploits some techniques related to natural language processing such as sentence similarity computation and sentence fusion. Our experimental results show that the proposed algorithms are effective.
APA, Harvard, Vancouver, ISO, and other styles
10

Shabanian, Mahdieh, and Seyed Hadi Hosseini. "Sensor Data Fusion Using Mutual Information Algorithm." Ciência e Natura 37 (December 19, 2015): 146. http://dx.doi.org/10.5902/2179460x20765.

Full text
Abstract:
Traffic flow prediction is one of the congestion avoidance methods in highways. According to previous studies, no comprehensive model has been proposed for traffic flow prediction which can prevent congestion in many different traffic conditions. Using data fusion to reduce prediction error is an interesting idea to solve this problem. In this paper, a new hybrid algorithm based on mutual information for traffic flow prediction will be proposed and compared with various types of previous hybrid algorithms and predictors. The Mutual Information (MI) algorithm is used to calculate the interdependency of data, so we expect this new hybrid algorithm to have high precision in comparison with others. Simulations will be implemented based on real data in MATLAB environment as a performance demonstration of new hybrid algorithm. Due to variety of traffic flow, performance investigations of our new hybrid algorithm will be done in presence of polluted traffic data in different climatic conditions such as rain/snow fall or other traffic conditions like congestions and accidents on the road, indicating robustness of this algorithm to different types of noisy data
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Data fusion algorithms"

1

Aziz, Ashraf Mamdouh Abdel. "New data fusion algorithms for distributed multi-sensor multi-target environments." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA369780.

Full text
Abstract:
Dissertation (Ph.D. in Electrical Engineering) Naval Postgraduate School, September 1999.
"September 1999". Dissertation supervisor(s): Robert Cristi, Murali Tummala. Includes bibliographical references (p. 199-214). Also avaliable online.
APA, Harvard, Vancouver, ISO, and other styles
2

Rivera, velázquez Josué. "Analysis and development of algorithms for data fusion in sensor arrays." Thesis, Montpellier, 2020. http://www.theses.fr/2020MONTS038.

Full text
Abstract:
Actuellement, la plupart des capteurs sont de nature `` intelligente '', ce qui signifie que les éléments de détection et l'électronique associée sont intégrés sur le même circuit. Parmi ces capteurs de nouvelle génération les systèmes micro-électro-mécaniques (MEMS) utilisent les technologies microélectroniques pour la fabrication par lots de capteurs à des volumes sans précédent et à des prix bas. Si ces composants sur étagère sont satisfaisants pour de nombreuses applications nécessitant un niveau de précision faible à moyen, ils ne peuvent toujours pas répondre pleinement aux besoins de performances de nombreuses applications de haute précision.Cependant, en raison de leur prix décroissant, de leur faible encombrement et de leur faible consommation d'énergie, il est désormais possible de mettre en œuvre des systèmes avec des dizaines ou même des centaines de capteurs. Ces systèmes amènent une solution possible au manque de performances des capteurs individuels et peuvent en outre améliorer la fiabilité et la robustesse de la détection. Les matrices de capteurs sont l'une de ces méthodes de mesures redondantes qui surviennent en réponse aux problèmes susmentionnés. Le développement d'algorithmes de fusion de données pour ces systèmes est un sujet de recherche fréquemment étudié dans la littérature. Néanmoins, il reste encore beaucoup de recherches à faire dans ce domaine de plus en plus important. L'émergence de nouvelles applications aux besoins de plus en plus complexes accroît la nécessité de nouveaux algorithmes avec des propriétés telles que la facilité d'intégration, l'adaptabilité, la robustesse, le faible coût de calcul et la généricité, entre autres.Dans cette thèse, nous présentons un nouvel algorithme pour les systèmes multi-capteurs qui propose une solution viable pour surmonter les contraintes mentionnées précédemment. La proposition est une méthode on-line basée sur une estimation quadratique sans biais de norme minimale (acronyme en Anglais: MINQUE) qui est capable de calculer les variances des capteurs sans connaître les entrées. Cet algorithme est capable de suivre les changements de variances des capteurs causés principalement par les effets du bruit basse fréquence, ainsi que de détecter et de signaler les capteurs affectés par des erreurs permanent ou transitoires. Cette approche est générique, ce qui signifie qu'elle peut être mise en œuvre pour différents types de systèmes de capteurs. De même, cet algorithme peut être implémenté dans des systèmes de réseaux de capteurs.Deux autres contributions de cette thèse peuvent être répertoriées. La première est un modèle de capteur générique pour les simulations de capteurs au niveau système. Cet outil créé dans l'environnement Matlab Simulink permet l'analyse des implémentations d'algorithmes de fusion de données dans des systèmes multi-capteurs. Contrairement aux modèles existant auparavant dans la littérature, ce modèle présente des caractéristiques telles que la généricité et l'inclusion de bruits basse fréquence, ainsi que le paramétrage à travers des graphiques d'analyse spectrale (graphique de Densité Spectrale de Puissance) et des graphiques d'analyse de stabilité dans le temps (graphique de l'écart Allan). La seconde est une étude visant à comparer les performances et la faisabilité de la mise en œuvre de différents algorithmes de fusion de données dans les systèmes multi-capteurs. Cette étude contient une analyse de la complexité de calcul, de la mémoire requise et de l'erreur d'estimation. Les algorithmes analysés sont : la méthode des moindres carrés, le réseau de neurones artificiel, le filtre de Kalman et la pondération aléatoire
Currently, most of the sensors are ``smart'' in nature, which means that sensing elements and associated electronics are integrated on the same chip. Among these new generation of sensors, the Micro-Electro-Mechanical-Systems (MEMS) make use of Microelectronics technologies for batch manufacturing of small footprint sensors to unprecedented volumes and at low prices. If those components of the shelf are satisfactory for many consumer and low- to medium-end applications, they still cannot fully meet the performance needs of many high-end applications.However, due to their decreasing price, their small footprint, and their low-power consumption, it is now feasible to implement systems with tens and even hundreds of sensors. Those systems give a possible solution to the lack of performance of individual sensors and additionally they can also improve dependability and robustness of sensing. Sensor array systems are one of these methods of redundant measurements that arise in response to the aforementioned problems. The development of data fusion algorithms for sensor array systems is a research topic frequently studied in the literature. Even so, it still remains a lot of research work to do in this increasingly important area. The emergence of new applications with increasingly complex needs is growing the requirement for new algorithms with features such as integration, adaptability, dependability, low computational cost, and genericity among others.In this thesis we present a new algorithm for sensor array systems that propose a viable solution to overcome constraints mentioned before. The proposal is an on-line method based on the MInimum Norm Quadratic Unbiased Estimation (MINQUE) that is able to compute sensors' variances without the knowledge of the inputs. This algorithm is capable to track changes in sensors' variances caused principally by the low-frequency noise effects, as well as to detect and point out sensors affected by permanent or transitory errors. This approach is generic, which means that it can be implemented for different types of sensor array systems. In addition, this algorithm can be also implemented in sensor network systems.Two more contributions of this thesis can be listed. The first is a generic sensor model for sensor simulations at system level. This tool created inside the Matlab Simulink environment permits the analysis of implementations of data fusion algorithms in multi-sensor systems. Unlike the models previously existing in the literature, this sensor model has characteristics such as genericity and inclusion of low-frequency noises. The second is a study to compare the performance and feasibility in the implementation of different algorithms for data fusion in sensor array systems. This study contains an analysis of computational complexity, memory required, and the error in estimation. The analyzed algorithms are : the method of least squares, an artificial neural network, Kalman filter, and Random weighting
APA, Harvard, Vancouver, ISO, and other styles
3

Baravdish, Ninos. "Information Fusion of Data-Driven Engine Fault Classification from Multiple Algorithms." Thesis, Linköpings universitet, Fordonssystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176508.

Full text
Abstract:
As the automotive industry constantly makes technological progress, higher demands are placed on safety, environmentally friendly and durability. Modern vehicles are headed towards increasingly complex system, in terms of both hardware and software making it important to detect faults in any of the components. Monitoring the engine’s health has traditionally been done using expert knowledge and model-based techniques, where derived models of the system’s nominal state are used to detect any deviations. However, due to increased complexity of the system this approach faces limitations regarding time and knowledge to describe the engine’s states. An alternative approach is therefore data-driven methods which instead are based on historical data measured from different operating points that are used to draw conclusion about engine’s present state. In this thesis a proposed diagnostic framework is presented, consisting of a systematically approach for fault classification of known and unknown faults along with a fault size estimation. The basis for this lies in using principal component analysis to find the fault vector for each fault class and decouple one fault at the time, thus creating different subspaces. Importantly, this work investigates the efficiency of taking multiple classifiers into account in the decision making from a performance perspective. Aggregating multiple classifiers is done solving a quadratic optimization problem. To evaluate the performance, a comparison with a random forest classifier has been made. Evaluation with challenging test data show promising results where the algorithm relates well to the performance of random forest classifier.
APA, Harvard, Vancouver, ISO, and other styles
4

Li, Lingjie Luo Zhi-Quan. "Data fusion and filtering for target tracking and identification /." *McMaster only, 2003.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Ayodeji, Akiwowo. "Developing integrated data fusion algorithms for a portable cargo screening detection system." Thesis, Loughborough University, 2012. https://dspace.lboro.ac.uk/2134/9901.

Full text
Abstract:
Towards having a one size fits all solution to cocaine detection at borders; this thesis proposes a systematic cocaine detection methodology that can use raw data output from a fibre optic sensor to produce a set of unique features whose decisions can be combined to lead to reliable output. This multidisciplinary research makes use of real data sourced from cocaine analyte detecting fibre optic sensor developed by one of the collaborators - City University, London. This research advocates a two-step approach: For the first step, the raw sensor data are collected and stored. Level one fusion i.e. analyses, pre-processing and feature extraction is performed at this stage. In step two, using experimentally pre-determined thresholds, each feature decides on detection of cocaine or otherwise with a corresponding posterior probability. High level sensor fusion is then performed on this output locally to combine these decisions and their probabilities at time intervals. Output from every time interval is stored in the database and used as prior data for the next time interval. The final output is a decision on detection of cocaine. The key contributions of this thesis includes investigating the use of data fusion techniques as a solution for overcoming challenges in the real time detection of cocaine using fibre optic sensor technology together with an innovative user interface design. A generalizable sensor fusion architecture is suggested and implemented using the Bayesian and Dempster-Shafer techniques. The results from implemented experiments show great promise with this architecture especially in overcoming sensor limitations. A 5-fold cross validation system using a 12 13 - 1 Neural Network was used in validating the feature selection process. This validation step yielded 89.5% and 10.5% true positive and false alarm rates with 0.8 correlation coefficient. Using the Bayesian Technique, it is possible to achieve 100% detection whilst the Dempster Shafer technique achieves a 95% detection using the same features as inputs to the DF system.
APA, Harvard, Vancouver, ISO, and other styles
6

Bougiouklis, Theodoros C. "Traffic management algorithms in wireless sensor networks." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FBougiouklis.pdf.

Full text
Abstract:
Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, September 2006.
Thesis Advisor(s): Weillian Su. "September 2006." Includes bibliographical references (p. 79-80). Also available in print.
APA, Harvard, Vancouver, ISO, and other styles
7

Elbakary, Mohamed Ibrahim. "Novel Pixel-Level and Subpixel-Level Registration Algorithms for Multi-Modal Imagery Data." Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1293%5F1%5Fm.pdf&type=application/pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Trailović, Lidija. "Ranking and optimization of target tracking algorithms." online access from Digital Dissertation Consortium access full-text, 2002. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?3074810.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Gnanapandithan, Nithya. "Data detection and fusion in decentralized sensor networks." Thesis, Manhattan, Kan. : Kansas State University, 2005. http://hdl.handle.net/2097/132.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Ho, Peter. "Organization in decentralized sensing." Thesis, University of Oxford, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306873.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Data fusion algorithms"

1

service), ScienceDirect (Online, ed. Image fusion: Algorithms and applications. Amsterdam: Academic Press/Elsevier, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Antony, Richard T. Principles of data fusion automation. Boston: Artech House, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Abdelgawad, Ahmed, and Magdy Bayoumi. Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-1350-9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Abdelgawad, Ahmed. Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks. Boston, MA: Springer US, 2012.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Klein, Lawrence A. Sensor and data fusion concepts and applications. Bellingham, Wash., USA: SPIE Optical Engineering Press, 1993.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Klein, Lawrence A. Sensor and data fusion concepts and applications. 2nd ed. Bellingham, Wash: SPIE, 1999.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Braun, Jerome J. Multisensor, multisource information fusion: Architectures, algorithms, and applications 2011 : 27-28 April 2011, Orlando, Florida, United States. Bellingham, Wash: SPIE, 2011.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Braun, Jerome J. Multisensor, multisource information fusion: Architectures, algorithms, and applications 2010 : 7-8 April 2010, Orlando, Florida, United States. Bellingham, Wash: SPIE, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

(Society), SPIE, ed. Multisensor, multisource information fusion: Architectures, algorithms, and applications 2009 : 16-17 April 2009, Orlando, Florida, United States. Bellingham, Wash: SPIE, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Michael, Gastpar, ed. Distributed source coding: Theory, algorithms, and applications. Amsterdam: Academic Press, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Data fusion algorithms"

1

Abdelgawad, Ahmed, and Magdy Bayoumi. "Proposed Centralized Data Fusion Algorithms." In Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks, 37–57. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-1350-9_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Abdelgawad, Ahmed, and Magdy Bayoumi. "Data Fusion in WSN." In Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks, 17–35. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-1350-9_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Beltz, Hayley, Timothy Rutledge, Raoul R. Wadhwa, Péter Bruck, Jan Tobochnik, Anikó Fülöp, György Fenyvesi, and Péter Érdi. "Ranking Algorithms: Application for Patent Citation Network." In Information Fusion and Data Science, 519–38. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03643-0_21.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Reddy, Dugimpudi Abhishek, Deepak Yadav, Nishi Yadav, and Devendra Kumar Singh. "Impact on Security Using Fusion of Algorithms." In Innovative Data Communication Technologies and Application, 577–85. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38040-3_65.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Clark, James J., and Alan L. Yuille. "Data Fusion in Shape From Shading Algorithms." In Data Fusion for Sensory Information Processing Systems, 147–80. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4757-2076-1_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Harris, Chris, Xia Hong, and Qiang Gan. "An introduction to modelling and learning algorithms." In Adaptive Modelling, Estimation and Fusion from Data, 1–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-18242-6_1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Clark, James J., and Alan L. Yuille. "Data Fusion Applied to Feature Based Stereo Algorithms." In Data Fusion for Sensory Information Processing Systems, 105–35. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4757-2076-1_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Segarra, David, Jessica Caballeros, Wilbert G. Aguilar, Albert Samà, and Daniel Rodríguez-Martín. "Orientation Estimation Using Filter-Based Inertial Data Fusion for Posture Recognition." In Algorithms for Sensor Systems, 220–33. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14094-6_15.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Fan, Jun, and Tiejun Huang. "A Fusion of Algorithms in Near Duplicate Document Detection." In New Frontiers in Applied Data Mining, 234–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28320-8_20.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Marasco, Emanuela, Ayman Abaza, Luca Lugini, and Bojan Cukic. "Impact of Biometric Data Quality on Rank-Level Fusion Schemes." In Algorithms and Architectures for Parallel Processing, 209–16. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03889-6_24.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Data fusion algorithms"

1

Bather, J. "Tracking and data fusion." In IEE International Seminar Target Tracking: Algorithms and Applications. IEE, 2001. http://dx.doi.org/10.1049/ic:20010234.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Julier, S. J. "Fusion without independence." In IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications. IEE, 2008. http://dx.doi.org/10.1049/ic:20080050.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

YADAV, S. SREEKRISHNA, and VIKAS MITTAL. "FPGA Implementation of Data Fusion Algorithms." In 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA). IEEE, 2019. http://dx.doi.org/10.1109/iceca.2019.8821858.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Judge, I. "RADIX - a solution to multiple sensor data fusion." In IEE International Seminar Target Tracking: Algorithms and Applications. IEE, 2001. http://dx.doi.org/10.1049/ic:20010231.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Alam, M. S. "Data fusion based target tracking in FLIR imagery." In Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2008. SPIE, 2008. http://dx.doi.org/10.1117/12.778390.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Atherton, D. P. "Data fusion for several Kalman filters tracking a single target." In Target Tracking 2004: Algorithms and Applications. IEE, 2004. http://dx.doi.org/10.1049/ic:20040053.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Du, Qian, John Ball, and Chiru Ge. "Hyperspectral and LiDAR data fusion using collaborative representation." In Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVI, edited by David W. Messinger and Miguel Velez-Reyes. SPIE, 2020. http://dx.doi.org/10.1117/12.2558967.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Ismail, Hesham, and Balakumar Balachandran. "Feature Extraction Algorithm Fusion for SONAR Sensor Data Based Environment Mapping." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-37116.

Full text
Abstract:
Mobile platforms that make use of concurrent localization and mapping algorithms have industrial applications for autonomous inspection and maintenance, such as the inspection of flaws and defects in oil pipelines and storage tanks. An important component of these algorithms is feature extraction, which involves detection of significant features that represent the environment. For example, points and lines can be used to represent features such as corners, edges, and walls. Feature extraction algorithms make use of relative position and angle data from sensor measurements gathered as the mobile vehicle traverses the environment. In this paper, sound navigation and ranging (SONAR) sensor data obtained from a mobile vehicle platform are considered for feature extraction and related algorithms are developed and studied. In particular, different combinations of commonly used feature extraction algorithms are examined to enhance the representation of the environment. The authors fuse the Triangulation Based Fusion (TBF), Hough Transfrom (HT), and SONAR salient feature extraction algorithms with the clustering algorithm. It is shown that the novel algorithm fusion can be used to capture walls, corners as well as features such as gaps in walls. This capability can be used to obtain additional information about the environment. Details of the algorithm fusion are discussed and presented along with results obtained through experiments.
APA, Harvard, Vancouver, ISO, and other styles
9

Dallil, A. "Combined evidential data association." In IET Conference on Data Fusion & Target Tracking 2014: Algorithms and Applications. Institution of Engineering and Technology, 2014. http://dx.doi.org/10.1049/cp.2014.0532.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Murphy, James M., and Mauro Maggioni. "Diffusion geometric methods for fusion of remotely sensed data." In Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, edited by David W. Messinger and Miguel Velez-Reyes. SPIE, 2018. http://dx.doi.org/10.1117/12.2305274.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Data fusion algorithms"

1

DVore, Ronald A. New Theory and Algorithms for Scalable Data Fusion. Fort Belvoir, VA: Defense Technical Information Center, June 2013. http://dx.doi.org/10.21236/ada587535.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Wainwright, Martin. New Theory and Algorithms for Scalable Data Fusion. Fort Belvoir, VA: Defense Technical Information Center, July 2013. http://dx.doi.org/10.21236/ada588861.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Yocky, D. A., M. D. Chadwick, S. P. Goudy, and D. K. Johnson. Multisensor data fusion algorithm development. Office of Scientific and Technical Information (OSTI), December 1995. http://dx.doi.org/10.2172/172138.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Chou, Fu-Mao. An Algorithm-Level Test Bed for Level-One Data Fusion Research (CASE-ATTI). Fort Belvoir, VA: Defense Technical Information Center, March 2001. http://dx.doi.org/10.21236/ada387790.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Chou, K. C., and A. S. Willsky. Multiscale Riccati Equations and a Two-Sweep Algorithm for the Optimal Fusion of Multiresolution Data. Fort Belvoir, VA: Defense Technical Information Center, February 1990. http://dx.doi.org/10.21236/ada459314.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Brown, Douglas, and Genetha Anne Gray. Implementation of a data fusion algorithm for RODS, a real-time outbreak and disease surveillance system. Office of Scientific and Technical Information (OSTI), October 2005. http://dx.doi.org/10.2172/876344.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Data fusion algorithms' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography