Multimodal biometrics combine a variety of biological features to have a significant impact
on identification performance, which is a newly developed trend in biometrics identification …

Multimodal biometrics provides rich information in biometric recognition systems, thus a
valid multimodal feature fusion framework and an efficient recognition algorithm are …

Multimodal biometrics recognition system suffers from the shortcomings of large data
processing and much time cost during the recognition. To overcome the shortcomings of the …

Extreme learning machine (ELM) as a new emergent and efficient machine learning
algorithm has shown its good performance in many real regression applications as well as …

Extreme learning machine (ELM) is one of the most important and efficient machine learning
algorithms for pattern classification due to its fast learning speed. In this paper, we propose a …

In a multimodal biometric recognition system, the integration of multiple features derived
from various biometric modalities seeks to overcome the several drawbacks found in a …

Multimodal biometrics combines a diversity of biological traits in an attempt to produce a
notable influence on identification performance. In recent years, multimodal biometric …

Metric learning has significantly improved machine learning applications such as face re-
identification and image classification using K-Nearest Neighbor (KNN) and Support Vector …

With the increasing demand for user recognition in several recent applications, experts
highly recommend using biometric identification technology in application development …

Multimodal biometrics is an evolving technology in the fields of security. Biometrics system
reduces the effort of remember a memorable password. Multimodal biometrics system uses …