Read e-book online Data Fusion for Situation Monitoring, Incident Detection, PDF

By E. Shahbazian, G. Rogova, P. Valin

ISBN-10: 1429405791

ISBN-13: 9781429405799

ISBN-10: 1586035363

ISBN-13: 9781586035365

Info Fusion is a really large interdisciplinary know-how area. It presents thoughts and strategies for; integrating details from a number of assets and utilizing the complementarities of those detections to derive greatest information regarding the phenomenon being saw; reading and deriving the that means of those observations and predicting attainable effects of the saw country of our surroundings; choosing the right plan of action; and controlling the activities. right here the focal point is at the extra mature part of information fusion, specifically the detection and identification/classification of phenomena being saw and exploitation of the comparable equipment for Security-Related Civil technological know-how and know-how (SST) functions. it is important to; extend at the information fusion method pertinent to scenario tracking, Incident Detection, Alert and reaction administration; speak about a few comparable Cognitive Engineering and visualization concerns; supply an perception into the architectures and methodologies for development an information fusion approach; speak about fusion techniques to photograph exploitation with emphasis on safety purposes; talk about novel disbursed monitoring ways as an important step of state of affairs tracking and incident detection; and supply examples of actual events, during which facts fusion can increase incident detection, prevention and reaction power. with a view to provide a logical presentation of the knowledge fusion fabric, first the final recommendations are highlighted (Fusion technique, Human desktop Interactions and platforms and Architectures), last with a number of functions (Data Fusion for Imagery, monitoring and Sensor Fusion and functions and possibilities for Fusion).IOS Press is a world technological know-how, technical and clinical writer of high quality books for teachers, scientists, and pros in all fields. a number of the parts we put up in: -Biomedicine -Oncology -Artificial intelligence -Databases and data structures -Maritime engineering -Nanotechnology -Geoengineering -All elements of physics -E-governance -E-commerce -The wisdom economic climate -Urban experiences -Arms keep watch over -Understanding and responding to terrorism -Medical informatics -Computer Sciences

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Read Online or Download Data Fusion for Situation Monitoring, Incident Detection, Alert and Response Management (NATO Science Series. 3: Computer and Systems Sciences) PDF

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Extra info for Data Fusion for Situation Monitoring, Incident Detection, Alert and Response Management (NATO Science Series. 3: Computer and Systems Sciences)

Example text

No application was identified clearly! My personal position was (and still is): for cases where multiple classifiers cannot improve performance, they can nonetheless increase reliability. Therefore, the use of MCS is just a matter of cost vs. benefit. MCSs are currently used in many applications; among others, sensor fusion, remote sensing, biometrics, documents analysis and OCR, data mining and KDD. However, one should ask: – – – after more than a decade of research in the MCS field, where do we stand?

Dasarathy, Decision Fusion, IEEE Computer Society Press, 1994. [27] Y. L. Marcialis, M. Pontil, P. Frasconi, F. Roli, Combining Flat and Structural Representations for Fingerprint Classification with Recursive Neural Networks and Support Vector Machine, Pattern Recognition, Vol. 36 (2), 2003, pp. 397–406. , Bagging Predictors, Machine Learning, 24, 123–140, 1996. E. Schapire, A decision-theoretic generalization of on-line learning and an application to boosting, Tech. Rep. AT&T Bell Labs, Murray Hill, NJ, 1995.

18 E. Blasch / Information Fusion for Decision Making or inappropriately combined, the user will make an incorrect analysis. Finally, if fusion quality is low, information validity, reliability, and trust is even lower. Using the techniques described in Section 4 fusion CAN DO: – – – – – – – – uncertainty reduction: gain knowledge from entropy info. reduction; detection: get a signal out of noise (signal detection theory); association: heterogeneous (across) & homogenous (within) fusion; correlation: covariance Error Analysis; estimation: filtering techniques (Kalman Filter) for prediction; combine data: add data for information such as data overlay; control: determine where to place sensors in real time; dimension reduction: reduce plethora of information to a smaller set.

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Data Fusion for Situation Monitoring, Incident Detection, Alert and Response Management (NATO Science Series. 3: Computer and Systems Sciences) by E. Shahbazian, G. Rogova, P. Valin

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