Segment-based Features

Segment-Based Features is a time series feature extraction method that derives descriptive characteristics by partitioning a time series into contiguous subsequences and computing statistical or structural metrics from each segment.

120

Publications

7.8K

Citations

410

Authors

204

Institutions

Publications per year

2017–2026

39

Authors

410

  1. SZ
    Shiqing Zhang

    Taizhou University, China

    3 publications · 624 citations

    3

    h-index

  2. GV
    George Vosselman

    University of Twente, Netherlands

    3 publications · 183 citations

    3

    h-index

  3. YY
    Yizhou Yu

    University of Hong Kong, Hong Kong SAR China

    2 publications · 865 citations

    2

    h-index

  4. YY
    Yifang Yin

    National University of Singapore, Singapore

    2 publications · 64 citations

    2

    h-index

  5. SC
    Shih‐Fu Chang

    Columbia University, United States

    2 publications · 1.1K citations

    2

    h-index

1–5 of 410

Venues

  1. IEEE Transactions on Affective Computing

    TAC · 4 publications · 298 citations

    4

    h-index

  2. IEEE Access

    4 publications · 99 citations

    4

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 333 citations

    3

    h-index

  4. International Journal of Remote Sensing

    3 publications · 200 citations

    3

    h-index

  5. Bioinformatics

    2 publications · 79 citations

    2

    h-index

1–5