Ayrulu, BirselBarshan, Billur2016-02-082016-02-082001-08http://hdl.handle.net/11693/27592Date of Conference: 20-22 Aug. 2001Conference name: Conference Documentation International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI 2001The comparison of different classification and fusion techniques was done for target classification and localization with sonar. Target localization performance of artificial neural networks (ANN) was found to be better than the target differentiation algorithm (TDA) and fusion techniques. The target classification performance of non-parametric approaches was better than that of parameterized density estimator (PDE) using homoscedastic and heteroscedastic NM for statistical pattern recognition techniques.EnglishArtificial neural networksEvidential reasoningLocalizationSensor data fusionSonarStatistical pattern recognitionTarget classificationVotingAlgorithmsClassification (of information)Neural networksPattern recognitionUltrasonic transducersIntelligent systemsSonarConference Paper10.1109/MFI.2001.1013503