Estimation and decision fusion: A survey

Authors:
Abhijit Sinha;Huimin Chen;D. G. Danu;Thia Kirubarajan;M. Farooq
Affiliations:
McMaster University, Hamilton, ON L8S 4K1 Canada;University of New Orleans, New Orleans, LA 70148, USA;McMaster University, Hamilton, ON L8S 4K1 Canada;McMaster University, Hamilton, ON L8S 4K1 Canada;Royal Military College of Canada, Kingston, ON K7K 5L0 Canada
Venue:
Neurocomputing
Year:
2008

Citing 22
Cited 8

The Strength of Weak Learnability

Machine Learning
Neural networks and the bias/variance dilemma

Neural Computation
Original Contribution: Stacked generalization

Neural Networks
Decision Combination in Multiple Classifier Systems

IEEE Transactions on Pattern Analysis and Machine Intelligence
Democracy in neural nets: voting schemes for classification

Neural Networks
Hierarchical mixtures of experts and the EM algorithm

Neural Computation
Classification by fuzzy integral: performance and tests

Fuzzy Sets and Systems - Special issue on fuzzy methods for computer vision and pattern recognition
Stacked regressions

Machine Learning
Bagging predictors

Machine Learning
On Combining Classifiers

IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Linear Combination of Neural Networks for Improving Classification Performance

IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-Level and Decision-Level Fusion of Noncoincidently Sampled Sensors for Land Mine Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Decision Fusion

Decision Fusion
On combining classifiers using sum and product rules

Pattern Recognition Letters
Multisensor Data Fusion

Multisensor Data Fusion
Neural Network Ensembles

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fusion of multiple classifiers for intrusion detection in computer networks

Pattern Recognition Letters
Mathematical Techniques in Multisensor Data Fusion (Artech House Information Warfare Library)

Mathematical Techniques in Multisensor Data Fusion (Artech House Information Warfare Library)
Boosting and other ensemble methods

Neural Computation
Switching between selection and fusion in combining classifiers: anexperiment

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Incremental learning with balanced update on receptive fields for multi-sensor data fusion

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Information combination operators for data fusion: a comparative review with classification

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Editorial: A representative bibliography of surveys in the information fusion domain

Information Fusion
Local rotation-based ensemble

International Journal of Knowledge Engineering and Data Mining
Applying dynamic reconfiguration in the mobile robotics domain: A case study on computer vision algorithms

ACM Transactions on Reconfigurable Technology and Systems (TRETS)
Dynamic world modelling by dichotomic information sets and graphical inference with focus on 3d facial pose tracking

SAMT'10 Proceedings of the 5th international conference on Semantic and digital media technologies
Affective modeling from multichannel physiology: analysis of day differences

ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
The decision fusion in the wireless network with possible transmission errors

Information Sciences: an International Journal
Decision fusion of sparse representation and support vector machine for SAR image target recognition

Neurocomputing
Classification of uncertain and imprecise data based on evidence theory

Neurocomputing

Quantified Score

Hi-index	0.01

Visualization

Abstract

Data fusion has been applied to a large number of fields and the corresponding applications utilize numerous mathematical tools. This survey focuses on some aspects of estimation and decision fusion. In estimation fusion, we discuss the development of fusion architectures and algorithms with emphasis on the cross-correlation between local estimates from different sources. On the other hand, the techniques for decision fusion are discussed with emphasis on the classifier combining techniques. In addition, methods using neural networks for data fusion are briefly discussed.