Signal Processing For Sensing

Signal Processing for Sensing is a computational methodology that transforms raw sensor data into meaningful information by filtering, analyzing, and interpreting signals specifically for the purpose of extracting context-aware, environment-related, or human-centric insights in mobile sensing applications.

59

Publications

3.4K

Citations

220

Authors

102

Institutions

Publications per year

2017–2026

25

Authors

220

  1. JX
    Jie Xiong

    University of Massachusetts Amherst, United States

    6 publications · 280 citations

    6

    h-index

  2. DZ
    Daqing Zhang

    Peking University, China

    4 publications · 225 citations

    4

    h-index

  3. FA
    Francesco Abate

    Columbia University, United States

    2 publications · 54 citations

    2

    h-index

  4. FZ
    Fusang Zhang

    Institute of Software, China

    2 publications · 110 citations

    2

    h-index

  5. GM
    Gustavo Monte

    National Technological University, Argentina

    2 publications · 54 citations

    2

    h-index

1–5 of 220

Venues

  1. IEEE Signal Processing Magazine

    4 publications · 393 citations

    4

    h-index

  2. IEEE Sensors Journal

    3 publications · 60 citations

    3

    h-index

  3. IEEE Transactions on Signal Processing

    2 publications · 60 citations

    2

    h-index

  4. 2

    h-index

  5. 2

    h-index

1–5