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Deep learning-based models have been very successful in achieving state-of-the-art results in many of the computer vision, speech recognition, and natural language processing tasks in the last few years. These models seem a natural fit for…
Neural Networks are the state of the art for many tasks in the computer vision domain, including Writer Identification (WI) and Writer Verification (WV). The transparency of these "black box" systems is important for improvements of…
Iris recognition is a secure biometric technology known for its stability and privacy. With no two irises being identical and little change throughout a person's lifetime, iris recognition is considered more reliable and less susceptible to…
The Iris pattern is a unique biological feature for each individual, making it a valuable and powerful tool for human identification. In this paper, an efficient framework for iris recognition is proposed in four steps. (1) Iris…
Pediatric wrist pathologies recognition from radiographs is challenging because normal anatomy changes rapidly with development: evolving carpal ossification and open physes can resemble pathology, and maturation timing differs by sex.…
Among many biometrics such as face, iris, fingerprint and others, periocular region has the advantages over other biometrics because it is non-intrusive and serves as a balance between iris or eye region (very stringent, small area) and the…
Biometry has proved its capability in terms of recognition accuracy. Now, it is widely used for automated border control with the biometric passport, to unlock a smartphone or a computer with a fingerprint or a face recognition algorithm.…
Biometric technologies are widely adopted in security, legal, and financial systems. Face recognition can authenticate a person based on the unique facial features such as shape and texture. However, recent works have demonstrated the…
As an advanced research topic in forensics science, automatic shoe-print identification has been extensively studied in the last two decades, since shoe marks are the clues most frequently left in a crime scene. Hence, these impressions…
Biometric recognition is the process of verifying or classifying human characteristics in images or videos. It is a complex task that requires machine learning algorithms, including convolutional neural networks (CNNs) and Siamese networks.…
Reliably identifying and verifying subjects remains integral to computer system security. Various novel authentication techniques, such as biometric authentication systems, have been developed in recent years. This paper provides a detailed…
Biometrics make human identification possible with a sample of a biometric trait and an associated database. Classical identification techniques lead to privacy concerns. This paper introduces a new method to identify someone using his…
In video-surveillance, person re-identification is the task of recognising whether an individual has already been observed over a network of cameras. Typically, this is achieved by exploiting the clothing appearance, as classical biometric…
The amount of secure data being stored on mobile devices has grown immensely in recent years. However, the security measures protecting this data have stayed static, with few improvements being done to the vulnerabilities of current…
A Bio-metrics system is actually a pattern recognition system that utilizes various patterns like iris, retina and biological traits like fingerprint, voice recognition, facial geometry and hand geometry. What makes Bio-metrics really…
3D face reconstruction algorithms from images and videos are applied to many fields, from plastic surgery to the entertainment sector, thanks to their advantageous features. However, when looking at forensic applications, 3D face…
Iris recognition of living individuals is a mature biometric modality that has been adopted globally from governmental ID programs, border crossing, voter registration and de-duplication, to unlocking mobile phones. On the other hand, the…
In the domain of Biometrics, recognition systems based on iris, fingerprint or palm print scans etc. are often considered more dependable due to extremely low variance in the properties of these entities with respect to time. However, over…
Recognizing handwritten digits is a challenging task primarily due to the diversity of writing styles and the presence of noisy images. The widely used MNIST dataset, which is commonly employed as a benchmark for this task, includes…
Detecting visual relationships between people and clothing in an image has been a relatively unexplored problem in the field of computer vision and biometrics. The lack readily available public dataset for ``worn'' and ``unworn''…