Semi-supervised learning of emblematic gestures

被引:5
|
作者
Al-Behadili, Husam [1 ]
Woehler, Christian [1 ]
Grumpe, Arne [1 ]
机构
[1] Tech Univ Dortmund, Fak Elektrotech & Informat Tech, Arbeitsgebiet Bildsignalverarbeitung, D-44227 Dortmund, Germany
关键词
Classification; gestures; polynomial classifier; confidence band; semi-supervised learning; RECOGNITION;
D O I
10.1515/auto-2014-1115
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This study describes a method for semi-supervised learning of three-dimensional emblematic gestures. Starting from a supervised learning stage using a small initial training set, the training set is extended fully automatically by employing a semi-supervised learning approach. Several criteria for acceptance or rejection of the class labels generated by the classifier are proposed. The experimental evaluation shows that the proposed semi-supervised learning approach yields an error rate which is only slightly higher than that of a classifier using all manually assigned class labels.
引用
收藏
页码:732 / 739
页数:8
相关论文
共 50 条
  • [1] Human Semi-Supervised Learning
    Gibson, Bryan R.
    Rogers, Timothy T.
    Zhu, Xiaojin
    TOPICS IN COGNITIVE SCIENCE, 2013, 5 (01) : 132 - 172
  • [2] Semi-supervised learning by disagreement
    Zhou, Zhi-Hua
    Li, Ming
    KNOWLEDGE AND INFORMATION SYSTEMS, 2010, 24 (03) : 415 - 439
  • [3] A survey on semi-supervised learning
    Jesper E. van Engelen
    Holger H. Hoos
    Machine Learning, 2020, 109 : 373 - 440
  • [4] A survey on semi-supervised learning
    Van Engelen, Jesper E.
    Hoos, Holger H.
    MACHINE LEARNING, 2020, 109 (02) : 373 - 440
  • [5] On semi-supervised learning
    A. Cholaquidis
    R. Fraiman
    M. Sued
    TEST, 2020, 29 : 914 - 937
  • [6] On semi-supervised learning
    Cholaquidis, A.
    Fraiman, R.
    Sued, M.
    TEST, 2020, 29 (04) : 914 - 937
  • [7] Adaptive Active Learning for Semi-supervised Learning
    Li Y.-C.
    Xiao F.
    Chen Z.
    Li B.
    Ruan Jian Xue Bao/Journal of Software, 2020, 31 (12): : 3808 - 3822
  • [8] Lagrangian supervised and semi-supervised extreme learning machine
    Ma, Jun
    Wen, Yakun
    Yang, Liming
    APPLIED INTELLIGENCE, 2019, 49 (02) : 303 - 318
  • [9] Feature ranking for semi-supervised learning
    Petkovic, Matej
    Dzeroski, Saso
    Kocev, Dragi
    MACHINE LEARNING, 2023, 112 (11) : 4379 - 4408
  • [10] RSSL: Semi-supervised Learning in R
    Krijthe, Jesse H.
    REPRODUCIBLE RESEARCH IN PATTERN RECOGNITION, RRPR 2016, 2017, 10214 : 104 - 115