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Browsing by Author "Afser, Huseyin"

Browsing by Author "Afser, Huseyin"

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  • A Baseline Statistical Method for Robust User-Assisted Multiple Segmentation 
    Afser, Huseyin (IEEE SIGNAL PROCESSING LETTERS / IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022)
    Recently, several image segmentation methods that welcome and leverage different types of user assistance have been developed. In these methods, the user inputs can be provided by drawing hounding boxes over image objects, ...
  • Kararlı Çoklu Bayes Hipotez Testi Üzerine Bir Not 
    Yildirim, Ugur; Afser, Huseyin (Avrupa Bilim ve Teknoloji Dergisi (EJOSAT) = European Journal of Science and Technology / Osman SAĞDIÇ, 2021-04)
    Çoklu Bayes hipotez testinde olasılık dağılımlarının bilindiği durumlar için optimum yöntemler bulunmasına karşın gerçek hayata uygulanması zordur. Bu yüzden gerçek dünyada iletişim sırasında kolaylıkla oluşabilecek gürültü ...
  • Polar Codes with Higher-Order Memory 
    Afser, Huseyin; Delic, Hakan (PROBLEMS OF INFORMATION TRANSMISSION / MAIK NAUKA/INTERPERIODICA/SPRINGER, 2018-10)
    We introduce a construction of a set of code sequences {C-n((m)) : n 1, m 1} with memory order m and code length N(n). {C-n((m))} is a generalization of polar codes presented by Arkan in [1], where the encoder mapping with ...
  • Some remarks on Bayesian multiple hypothesis testing 
    Afser, Huseyin (Hacettepe Journal of Mathematics and Statistics / Hacettepe Üniversitesi, 2022-02)
    We consider Bayesian multiple hypothesis problem with independent and identically distributed observations. The classical, Sanov's theorem-based, analysis of the error probability allows one to characterize the best ...
  • Statistical Classification via Robust Hypothesis Testing: Non-Asymptotic and Simple Bounds 
    Afser, Huseyin (IEEE SIGNAL PROCESSING LETTERS / IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2021-10)
    We consider Bayesian multiple statistical classification problem in the case where the unknown source distributions are estimated from the labeled training sequences, then the estimates are used as nominal distributions ...