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[학술저널]

스마트폰 로봇의 위치 인식을 위한 준 지도식 학습 기법

  • 학술저널

스마트폰 로봇의 위치 인식을 위한 준 지도식 학습 기법

Semi-supervised Learning for the Positioning of a Smartphone-based Robot

유재현(서울대학교) 김현진(서울대학교)

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초록

Supervised machine learning has become popular in discovering context descriptions from sensor data. However, collecting a large amount of labeled training data in order to guarantee good performance requires a great deal of expense and time. For this reason, semi-supervised learning has recently been developed due to its superior performance despite using only a small number of labeled data. In the existing semi-supervised learning algorithms, unlabeled data are used to build a graph Laplacian in order to represent an intrinsic data geometry. In this paper, we represent the unlabeled data as the spatial-temporal dataset by considering smoothly moving objects over time and space. The developed algorithm is evaluated for position estimation of a smartphone-based robot. In comparison with other state-of-art semi-supervised learning, our algorithm performs more accurate location estimates.

목차

Abstract
Ⅰ. 서론
Ⅱ. 준 지도식 학습기법 개요
Ⅲ. Laplacian Embedded Regularized Least Square (LapERLS)
Ⅳ. Time series LapERLS
Ⅴ. 와이파이 신호를 이용한 위치 추정
Ⅵ. 파라미터 튜닝
Ⅶ. 실험 결과
Ⅷ. 결론
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