A-iLearn: An adaptive incremental learning model for spoof fingerprint detection
Incremental learning enables the learner to accommodate new knowledge without retraining the existing model. It is a challenging task that requires learning from new data and preserving the knowledge extracted from the previously accessed data. This challenge is known as the stability-plasticity dil...
Enregistré dans:
Auteurs principaux: | Shivang Agarwal, Ajita Rattani, C. Ravindranath Chowdary |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Elsevier
2022
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/b7ba07c72783430c8d1e5af62c2dcb49 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
T-DFNN: An Incremental Learning Algorithm for Intrusion Detection Systems
par: Mahendra Data, et autres
Publié: (2021) -
A divided and prioritized experience replay approach for streaming regression
par: Mikkel Leite Arnø, et autres
Publié: (2021) -
Application Research on Optimization Algorithm of sEMG Gesture Recognition Based on Light CNN+LSTM Model
par: Dianchun Bai, et autres
Publié: (2021) -
Live Spoofing Detection for Automatic Human Activity Recognition Applications
par: Viktor Dénes Huszár, et autres
Publié: (2021) -
Using Rounding Errors in Modern Computer Technologies
par: Valerii Zadiraka, et autres
Publié: (2021)