IDENTITY PREDICTION FROM ONLINE HANDWRITING BIOMETRICS / SUFIAN OLAYINKA IBRAHIM ; SUPERVISOR, ASST. PROF. DR. YASEMIN BAY AZYEREN

Yazar: Katkıda bulunan(lar):Dil: İngilizce 2024Tanım: 53 sheets; + 1 CD ROM 30 cmİçerik türü:
  • text
Ortam türü:
  • unmediated
Taşıyıcı türü:
  • volume
Konu(lar): Tez notu: Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Management Information Systems Özet: In the quickly changing world of today, it is more important than ever to correctly determine and confirm people's identities. By leading the development of an advanced system that uses online handwriting biometrics to dramatically alter the identity prediction process, this project is well-positioned to address this growing requirement. The core of this project is a thorough investigation of 42 unique characteristics that are present in the field of online handwriting biometrics. The project attempts to find and prioritize the most discriminative features, guaranteeing the robustness and reliability of the final system, through careful research and rigorous testing. Focusing on these essential characteristics will allow the system to capture the core of a person's handwriting style, making it highly confident in its ability to forecast that person's identity. The use of cutting-edge classification approaches, which will form the foundation of the identification prediction process, is essential to the project's success. By utilizing methods from pattern recognition and machine learning, these approaches will sort through enormous volumes of data and identify minute connections and patterns that could escape human scrutiny. Iteratively improving and optimizing, the system will keep improving its ability to predict handwriting patterns, allowing it to adjust to changing situations and be useful in a variety of settings. The goal of this project is to transform identity authentication by establishing a connection between state-of-the-art technical innovations and conventional verification techniques. Creating a framework that is more inclusive and accessible to everyone is the ultimate aim, going beyond simply optimizing current procedures. With the ability to improve security, fight fraud, and preserve the integrity of vital systems and services, this technology has a wide range of potential uses in the fields of banking, healthcare, and law enforcement. Essentially, this initiative marks a paradigm shift in how we address the fundamental subject of identity verification in the digital era, representing more than just a technological advance. In an increasingly connected world, we have the chance to not only improve and expedite current procedures but also open up new avenues for security, effectiveness, and trust by utilizing online handwriting biometrics.
Materyal türü: Thesis
Mevcut
Materyal türü Geçerli Kütüphane Koleksiyon Yer Numarası Kopya numarası Durum Notlar İade tarihi Barkod Materyal Ayırtmaları
Thesis Thesis CIU LIBRARY Depo Tez Koleksiyonu YL 3453 I27 2024 (Rafa gözat(Aşağıda açılır)) C.1 Kullanılabilir Management Information Systems T3870
Suppl. CD Suppl. CD CIU LIBRARY Görsel İşitsel Tez Koleksiyonu YL 3453 I27 2024 (Rafa gözat(Aşağıda açılır)) C.1 Kullanılabilir Management Information Systems CDT3870
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Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Management Information Systems

In the quickly changing world of today, it is more important than ever to correctly determine and confirm people's identities. By leading the development of an advanced system that uses online handwriting biometrics to dramatically alter the identity prediction process, this project is well-positioned to address this growing requirement. The core of this project is a thorough investigation of 42 unique characteristics that are present in the field of online handwriting biometrics. The project attempts to find and prioritize the most discriminative features, guaranteeing the robustness and reliability of the final system, through careful research and rigorous testing. Focusing on these essential characteristics will allow the system to capture the core of a person's handwriting style, making it highly confident in its ability to forecast that person's identity. The use of cutting-edge classification approaches, which will form the foundation of the identification prediction process, is essential to the project's success. By utilizing methods from pattern recognition and machine learning, these approaches will sort through enormous volumes of data and identify minute connections and patterns that could escape human scrutiny. Iteratively improving and optimizing, the system will keep improving its ability to predict handwriting patterns, allowing it to adjust to changing situations and be useful in a variety of settings. The goal of this project is to transform identity authentication by establishing a connection between state-of-the-art technical innovations and conventional verification techniques. Creating a framework that is more inclusive and accessible to everyone is the ultimate aim, going beyond simply optimizing current procedures. With the ability to improve security, fight fraud, and preserve the integrity of vital systems and services, this technology has a wide range of potential uses in the fields of banking, healthcare, and law enforcement. Essentially, this initiative marks a paradigm shift in how we address the fundamental subject of identity verification in the digital era, representing more than just a technological advance. In an increasingly connected world, we have the chance to not only improve and expedite current procedures but also open up new avenues for security, effectiveness, and trust by utilizing online handwriting biometrics.

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