کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
529307 869644 2007 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An optimized architecture for classification combining data fusion and data-mining
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
An optimized architecture for classification combining data fusion and data-mining
چکیده انگلیسی

This paper presents a new architecture to integrate a library of feature extraction, Data-mining, and fusion techniques to automatically and optimally configure a classification solution for a given labeled set of training patterns. The most expensive and scarce resource in any detection problem (feature selection/classification) tends to be the acquiring of labeled training patterns from which to design the system. The objective of this paper is to present a new Data-mining architecture that will include conventional Data-mining algorithms, feature selection methods and algorithmic fusion techniques to best exploit the set of labeled training patterns so as to improve the design of the overall classification system. The paper describes how feature selection and Data-mining algorithms are combined through a Genetic Algorithm, using single source data, and how multi-source data are combined through several best-suited fusion techniques by employing a Genetic Algorithm for optimal fusion. A simplified version of the overall system is tested on the detection of volcanoes in the Magellan SAR database of Venus.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Fusion - Volume 8, Issue 4, October 2007, Pages 366–378
نویسندگان
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