skip to main content
Skip header Section
Mathematical Techniques in Multisensor Data FusionFebruary 1992
Publisher:
  • Artech House, Inc.
  • 685 Canton St. Norwood, MA
  • United States
ISBN:978-0-89006-558-7
Published:01 February 1992
Pages:
326
Skip Bibliometrics Section
Bibliometrics
Skip Abstract Section
Abstract

From the Publisher:

This invaluable reference offers the most comprehensive introduction available to the concepts of multisensor data fusion. It introduces key algorithms, provides advice on their utilization, and raises issues associated with their implementation. With a diverse set of mathematical and heuristic techniques for combining data from multiple sources, the book shows how to implement a data fusion system, describes the process for algorithm selection, functional architectures and requirements for ancillary software, and illustrates man-machine interface requirements an database issues.

Cited By

  1. ACM
    Fan G, Song X, Zhao Y, Yan Z and Wang X Ship Fusion Recognition Based on AIS Data and Remote Sensing Image Proceedings of the 2022 6th International Conference on Computer Science and Artificial Intelligence, (116-120)
  2. ACM
    Liu C, Ma R, Hu B and Fan Q Multivariate Data Fusion Method Based on 3DGIS and its Application in Engineering Management Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering, (1393-1397)
  3. ACM
    Pham H, Moore P and Tran K Context matching with reasoning and decision support using hedge algebra with Kansei evaluation Proceedings of the 5th Symposium on Information and Communication Technology, (202-210)
  4. Rodger J (2012). Toward reducing failure risk in an integrated vehicle health maintenance system, Expert Systems with Applications: An International Journal, 39:10, (9821-9836), Online publication date: 1-Aug-2012.
  5. Hyland J and Smith C System performance and layered analysis tool Proceedings of the Winter Simulation Conference, (2600-2611)
  6. Elmas Ç and Sönmez Y (2011). A data fusion framework with novel hybrid algorithm for multi-agent Decision Support System for Forest Fire, Expert Systems with Applications: An International Journal, 38:8, (9225-9236), Online publication date: 1-Aug-2011.
  7. Jiang S, Zhang C and Zhang S (2011). Two-stage structural damage detection using fuzzy neural networks and data fusion techniques, Expert Systems with Applications: An International Journal, 38:1, (511-519), Online publication date: 1-Jan-2011.
  8. Steffens M, Krybus W and Kohring C Dynamic world modelling by dichotomic information sets and graphical inference with focus on 3d facial pose tracking Proceedings of the 5th international conference on Semantic and digital media technologies, (159-172)
  9. Chen P, Krim H and Mendoza O (2010). Multiphase joint segmentation-registration and object tracking for layered images, IEEE Transactions on Image Processing, 19:7, (1706-1719), Online publication date: 1-Jul-2010.
  10. Ji Z and Jonathan Wu Q (2010). An improved artificial immune algorithm with application to multiple sensor systems, Information Fusion, 11:2, (174-182), Online publication date: 1-Apr-2010.
  11. Malek A and Yashtini M (2010). Image fusion algorithms for color and gray level images based on LCLS method and novel artificial neural network, Neurocomputing, 73:4-6, (937-943), Online publication date: 1-Jan-2010.
  12. Pantziou G, Mpitziopoulos A, Gavalas D, Konstantopoulos C and Mamalis B Mobile Sinks for Information Retrieval from Cluster-Based WSN Islands Proceedings of the 8th International Conference on Ad-Hoc, Mobile and Wireless Networks, (213-226)
  13. Murad N Low energy clustering adaptation protocol for an adhoc wireless sensor network Proceedings of the 2009 conference on Wireless Telecommunications Symposium, (136-142)
  14. Thomas C and Balakrishnan N Mathematical analysis of sensor fusion for intrusion detection systems Proceedings of the First international conference on COMmunication Systems And NETworks, (147-156)
  15. Zhu Y, Bull M, Akin H, Sepúlveda J and Rabelo L Information fusion in underwater sonar simulation Proceedings of the 40th Conference on Winter Simulation, (1250-1258)
  16. ACM
    Nakamura E and Loureiro A Information fusion in wireless sensor networks Proceedings of the 2008 ACM SIGMOD international conference on Management of data, (1365-1372)
  17. Wu X, Wang P, Wang W and Shi B Data-aware clustering hierarchy for wireless sensor networks Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining, (795-802)
  18. Akin H, Bull M, Rabelo L, Sepúlveda J and Zhu Y Integrating simulation and geographic information system Proceedings of the 2008 Spring simulation multiconference, (648-655)
  19. Zhang X, Niu Z, Xu X, Zhao K and Cao Y The research of the sensor fusion model based on fuzzycomprehensive theory Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications, (396-402)
  20. ACM
    Nakamura E, Loureiro A and Frery A (2007). Information fusion for wireless sensor networks, ACM Computing Surveys (CSUR), 39:3, (9-es), Online publication date: 3-Sep-2007.
  21. Hwang S, Lu K, Chang H and Dow C An efficient grid-based data gathering scheme in wireless sensor networks Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing, (545-556)
  22. Sun P, Zhao H, Zhang X, Xu J, Yin Z, Zhang X and Zhu S The Research of Decision Information Fusion Algorithm Based on the Fuzzy Neural Networks Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks, (234-240)
  23. Aziz A (2007). Fuzzy track-to-track association and track fusion approach in distributed multisensor-multitarget multiple-attribute environment, Signal Processing, 87:6, (1474-1492), Online publication date: 1-Jun-2007.
  24. Minners H and Mackey D Conceptual linking of FCS C4ISR systems performance to information quality and force effectiveness using the CASTFOREM high resolution combat model Proceedings of the 38th conference on Winter simulation, (1222-1225)
  25. ACM
    Yu B, Scerri P, Sycara K, Xu Y and Lewis M Scalable and reliable data delivery in mobile ad hoc sensor networks Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems, (1071-1078)
  26. Zhang D, Zeng G, Ban X and Yin Y A kind of context-aware approach based on fuzzy-neural for proactive service of pervasive computing Proceedings of the Second international conference on Embedded Software and Systems, (554-563)
  27. ACM
    Yu D and Frincke D Alert confidence fusion in intrusion detection systems with extended Dempster-Shafer theory Proceedings of the 43rd annual Southeast regional conference - Volume 2, (142-147)
  28. ACM
    Siaterlis C and Maglaris B Towards multisensor data fusion for DoS detection Proceedings of the 2004 ACM symposium on Applied computing, (439-446)
  29. Clouqueur T, Saluja K and Ramanathan P (2004). Fault Tolerance in Collaborative Sensor Networks for Target Detection, IEEE Transactions on Computers, 53:3, (320-333), Online publication date: 1-Mar-2004.
  30. Dekhtyar A, Goldsmith J and Pearce J (2003). When plans distinguish Bayes nets, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11:Supplement, (1-24), Online publication date: 1-Nov-2003.
  31. Chang K, Bowyer K and Flynn P Multi-Modal 2D and 3D Biometrics for Face Recognition Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
  32. Dou W, Ruan S, Liao Q, Bloyet D, Constans J and Chen Y Fuzzy information fusion scheme used to segment brain tumor from MR images Proceedings of the 5th international conference on Fuzzy Logic and Applications, (208-215)
  33. Stefano C, Cioppa A and Marcelli A Exploiting Reliability for Dynamic Selection of Classifiers by Means of Genetic Algorithms Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
  34. Achalakul T and Taylor S (2003). A distributed spectral-screening PCT algorithm, Journal of Parallel and Distributed Computing, 63:3, (373-384), Online publication date: 1-Mar-2003.
  35. Gunatilaka A and Baertlein B (2001). Feature-Level and Decision-Level Fusion of Noncoincidently Sampled Sensors for Land Mine Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23:6, (577-589), Online publication date: 1-Jun-2001.
  36. Shen H and Wang X (2019). Multiple Hypotheses Testing Method for Distributed Multisensor Systems, Journal of Intelligent and Robotic Systems, 30:2, (119-141), Online publication date: 1-Feb-2001.
  37. ACM
    Aslandogan Y and Yu C Evaluating strategies and systems for content based indexing of person images on the Web Proceedings of the eighth ACM international conference on Multimedia, (313-321)
  38. Chung A and Shen H (2019). Entropy-Based Markov Chains for Multisensor Fusion, Journal of Intelligent and Robotic Systems, 29:2, (161-189), Online publication date: 1-Oct-2000.
  39. Marchand Y and Damper R (2000). A multistrategy approach to improving pronunciation by analogy, Computational Linguistics, 26:2, (195-219), Online publication date: 1-Jun-2000.
  40. Neti C, Maison B, Senior A, Iyengar G, Decuetos P, Basu S and Verma A Joint processing of audio and visual information for multimedia indexing and human-computer interaction Content-Based Multimedia Information Access - Volume 1, (294-301)
  41. ACM
    Bass T (2000). Intrusion detection systems and multisensor data fusion, Communications of the ACM, 43:4, (99-105), Online publication date: 1-Apr-2000.
  42. Blackmond Laskey K, D'Ambrosio B, Levitt T and Mahoney S (2019). Limited Rationality in Action, Minds and Machines, 10:1, (53-77), Online publication date: 1-Feb-2000.
Contributors

Recommendations