FSR vehicles classification system based on hybrid neural network with different data extraction methods

FSR vehicles classification system based on hybrid neural network with different data extraction methods

This paper evaluates the performance of Forward Scatter Radar classification system using as so called 'hybrid FSR classification techniques' based on three different data extraction methods which are manual, Principal Component Analysis (PCA) and z-score. By combining these data extractio...

詳細記述

書誌詳細
出版年:Proceeding - 2017 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2017
第一著者: Abdullah N.F.; Rashid N.E.A.; Ibrahim I.P.; Abdullah R.S.A.R.
フォーマット: Conference paper
言語:English
出版事項: Institute of Electrical and Electronics Engineers Inc. 2017
オンライン･アクセス:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049608648&doi=10.1109%2fICRAMET.2017.8253138&partnerID=40&md5=c9527d8a9f10fe022a7009691e2d3e1f

インターネット

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049608648&doi=10.1109%2fICRAMET.2017.8253138&partnerID=40&md5=c9527d8a9f10fe022a7009691e2d3e1f

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