Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …

Recently, biometric verification systems have been widely used in security applications with
multi-level authentication. Existing machine learning approaches were utilized to develop …

Biometric authentication is becoming the crucial technology in real world applications, which
includes automation and security. However, the various works are implemented the …

Although the Mask region-based convolutional neural network (R-CNN) model possessed a
dominant position for complex and variable road scene segmentation, some problems still …

Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing
capabilities. Additionally, it leverages inter-modal correlation to enhance recognition …

Biometric identification technology has become a common part of daily life due to the global
demand for information security and security legislation. Due to its capacity to circumvent …

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Informatica 47 (2023) 417- 430 417 Deep Learning-Based CNN Multi-Modal Camera Model …

Conventional biometric systems are vulnerable to a range of harmful threats and privacy
violations, putting the users who have registered with them in grave danger. Therefore, there …

Multi-modal biometric system combines feature knowledge indifferent traits to conquer the
deficienciesof unimodal systems. But, over the last few years, the conventional biometric …

This study delves into the complex issue posed by facial makeup, which has the potential to
significantly alter the appearance of individuals, posing a challenge to automated face …