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2014 Fiscal Year Final Research Report

novel probability Pattern Recognition derived from a density function consisting with normal samples and their mirror ones

Research Project

  • PDF
Project/Area Number 24500338
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Statistical science
Research InstitutionTokyo University of Agriculture and Technology

Principal Investigator

SEIJI Hotta  東京農工大学, 工学(系)研究科(研究院), 准教授 (90346932)

Project Period (FY) 2012-04-01 – 2015-03-31
Keywordsパターン認識
Outline of Final Research Achievements

This research presents a novel probability density function (PDF) consisting with normal samples and their mirror ones. We can derive heuristic classifiers such as simple and multiple subspace classifiers from this PDF. The performance of our approach is verified by experiments on big data recognition such as image, audio, and video.

Free Research Field

情報科学

URL: 

Published: 2016-06-03  

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