Logistic Regression-based Detection

Logistic Regression-Based Detection is a methodological approach within statistical pattern recognition that employs logistic regression models to classify or identify occurrences of specific phenomena by estimating the probability of an event based on input predictors.

39

Publications

1.4K

Citations

155

Authors

73

Institutions

Publications per year

2017–2026

27

Authors

155

  1. CA
    Cheri A. Levinson

    University of Louisville, United States

    1 publications · 20 citations

    1

    h-index

  2. MD
    M. Devika

    Siddhartha Medical College, India

    1 publications · 21 citations

    1

    h-index

  3. VP
    V. Paul Doria‐Rose

    National Cancer Institute, United States

    1 publications · 14 citations

    1

    h-index

  4. RM
    Rabiu Muazu Musa

    Universiti Malaysia Pahang Al-Sultan Abdullah, Malaysia

    1 publications · 13 citations

    1

    h-index

  5. YD
    Yousuf D. Almoallem

    Smith-Kettlewell Eye Research Institute, United States

    1 publications · 31 citations

    1

    h-index

1–5 of 155

Venues

  1. Computers & Security

    2 publications · 207 citations

    2

    h-index

  2. IATSS Research

    1 publications · 51 citations

    1

    h-index

  3. Computational Intelligence

    1 publications · 37 citations

    1

    h-index

  4. 1

    h-index

  5. Expert Systems with Applications

    1 publications · 47 citations

    1

    h-index

1–5