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Browsing M.S. Theses by Subject "Pattern recognition systems."

Browsing M.S. Theses by Subject "Pattern recognition systems."

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  • A biometric authentication technique using spread spectrum audio watermarking 
    Can, Yekta Said. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2014., 2014.)
    Watermarking has become important in the last decade because of the copyright protection applications. Embedding information into an audio le is more di cult as compared to images, because human auditory system is more ...
  • Computer vision based multi-lingual fingerspelling recognition 
    Kındıroğlu, Ahmet Alp. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2011., 2011.)
    In this thesis, we focus on the problem of computer vision based automatic signlanguage recognition and its related subtasks. The study focuses on the recognition of ngerspelling gestures, which are a subset of sign ...
  • Facial feature tracking and expression recognition for sign language 
    Arı, İsmail. (Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2008., 2008.)
    Extracting and tracking facial features in image sequences automatically is a required first step in many applications including expression classification. When sign language recognition is concerned, expressions imply ...
  • Geometry based hand vein biometry 
    Sağlam, Pınar. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2012., 2012.)
    This thesis documents a study in which new algorithms are developed for geometry based hand vein biometry. Hand vein patterns are assumed not to change over time except in their size, and they are unique to each individual, ...
  • Nonlinear dimensionality reduction methods for pattern recognition 
    Turhan, Burak. (Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2004., 2004.)
    The aim of dimensionality reduction is to find a lower dimensional, simpler representation while keeping the important information in the data. It is essential to employ dimensionality reduction for high dimensional data ...

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