Deep Learning algorithms (DL) have been applied in different domains such as computer
vision, image detection, robotics and speech processing, in most cases, DL demonstrated …

Nowadays, there has been an increase in security concerns regarding fingerprint biometrics.
This problem arises due to technological advancements in bypassing and hacking …

This paper introduces an intelligent computational approach to automatically authenticate
fingerprint for personal identification and verification. The feature vector is formed using …

In all biometric traits, a fingerprint is considered as a foremost trait due to its high security
level, reliability, universality, uniqueness, robustness, low costs, and user convenience. Due …

The accuracy of fingerprint recognition model is extremely important due to its usage in
forensic and security fields. Any fingerprint recognition system has particular network …

Fingerprint classification plays a fundamental role in fingerprint identification systems
because it dramatically reduces the time spent identifying an individual. This classification …

The fingerprint identification is the most widely used authentication system. The fingerprint
uniqueness for each human being provides error-free identification. However, during the …

Fingerprint classification helps in reducing the number of comparisons during the matching
stage in automatic fingerprint identification system. In this study, a convolutional neural …

Biometrics is a field of research that focuses on the analysis of an individual's identity which
is based on a feature vector that contains characteristics derived from behavioural or …

Fingerprint recognition has been utilized for cellphone authentication, airport security and
beyond. Many different features and algorithms have been proposed to improve fingerprint …