연구동향 분석

스마트폰 센서를 이용한 사용자 행위 기반 개인 분류 기법의 성능 평가

김영인 2018년

논문상세정보
    • 저자 김영인
    • 제어번호 105967052
    • 학술지명 한국지식정보기술학회 논문지
    • 권호사항 Vol. 13 No. 6 [ 2018 ]
    • 발행처 한국지식정보기술학회
    • 자료유형 학술저널
    • 수록면 835-845 ( 11쪽)
    • 언어 Korean
    • 출판년도 2018
    • 등재정보 KCI등재
    • 판매처
    유사주제 논문( 0)
인용/피인용

' 스마트폰 센서를 이용한 사용자 행위 기반 개인 분류 기법의 성능 평가' 의 참고문헌

  • The WEKA workbench. Online appendix for data mining: Practical machine learning tools and techniques
    E. Frank [2016]
  • Recent trends in machine learning for human activity recognition—A survey
  • Real-time human activity recognition from accelerometer data using Convolutional Neural Networks
    A. Ignatov [2018]
  • Personalization and user verification in wearable systems using biometric walking patterns
    P. Casale [2012]
  • Personal authentication technology and database construction using biosignals
    J-H. Kim [2016]
  • Person recognition using smartphones' accelerometer data
  • On the instability of sensor orientation in gait verification on mobile phone
    T. Hoang [2015]
  • Implicit sensor-based authentication of smartphone users with smartwatch
    W. H. Lee [2016]
  • Identifying smartphone users based on their activity patterns via mobile sensing
  • How many trees in a random forest?
  • Data mining for business intelligence: Concepts, techniques, and applications in Microsoft Office Excel with XLMiner
    G. Shmueli [2011]
  • Cell phone-based biometric identification
  • An empirical evaluation of activities and classifiers for user identification on smartphones
    C. Tang [2016]
  • A study of cross-validation and bootstrap for accuracy estimation and model selection
    R. Kohavi [1995]
  • A comprehensive analysis on wearable acceleration sensors in human activity recognition
  • A Public Domain Dataset for Human Activity Recognition Using Smartphones
    D. Anguita [2013]