Adaptive Detection Systems

Adaptive Detection Systems is a computational framework in money laundering detection that dynamically updates its analytical models and decision rules in response to evolving transaction patterns and emerging typologies, thereby enhancing detection accuracy over time through continuous learning from new data.

222

Publications

10.7K

Citations

514

Authors

260

Institutions

Publications per year

2017–2026

60

Authors

514

  1. DO
    Danilo Orlando

    University Niccolò Cusano, Italy

    19 publications · 1.1K citations

    17

    h-index

  2. AD
    Antonio De Maio

    University of Naples Federico II, Italy

    17 publications · 1.4K citations

    16

    h-index

  3. CH
    Chengpeng Hao

    Chinese Academy of Sciences, China

    15 publications · 750 citations

    15

    h-index

  4. GR
    Giuseppe Ricci

    University of Salento, Italy

    12 publications · 1K citations

    12

    h-index

  5. JL
    Jun Liu

    University of Science and Technology of China, China

    10 publications · 475 citations

    10

    h-index

1–5 of 514

Venues

  1. IEEE Transactions on Signal Processing

    34 publications · 2.4K citations

    27

    h-index

  2. 18

    h-index

  3. IEEE Signal Processing Letters

    17 publications · 1.3K citations

    13

    h-index

  4. Signal Processing

    10 publications · 259 citations

    9

    h-index

  5. IET Radar Sonar & Navigation

    8 publications · 271 citations

    8

    h-index

1–5