BUIR logo
Communities & Collections
All of BUIR
  • English
  • Türkçe
Log In
Please note that log in via username/password is only available to Repository staff.
Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Ge, Y."

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    ItemOpen Access
    Reliable extraction of semantic information and rate of innovation estimation for graph signals
    (Institute of Electrical and Electronics Engineers , 2022-12-19) Kalfa, Mert ; Yetim, Sadık Yağız ; Atalik, Arda ; Gök, Mehmetcan; Ge, Y.; Li, R.; Tong, W.; Duman, Tolga Mete; Arıkan, Orhan
    Semantic signal processing and communications are poised to play a central part in developing the next generation of sensor devices and networks. A crucial component of a semantic system is the extraction of semantic signals from the raw input signals, which has become increasingly tractable with the recent advances in machine learning (ML) and artificial intelligence (AI) techniques. The accurate extraction of semantic signals using the aforementioned ML and AI methods, and the detection of semantic innovation for scheduling transmission and/or storage events are critical tasks for reliable semantic signal processing and communications. In this work, we propose a reliable semantic information extraction framework based on our previous work on semantic signal representations in a hierarchical graph-based structure. The proposed framework includes a time integration method to increase fidelity of ML outputs in a class-aware manner, a graph-edit-distance based metric to detect innovation events at the graph-level and filter out sporadic errors, and a Hidden Markov Model (HMM) to produce smooth and reliable graph signals. The proposed methods within the framework are demonstrated individually and collectively through simulations and case studies based on real-world computer vision examples.

About the University

  • Academics
  • Research
  • Library
  • Students
  • Stars
  • Moodle
  • WebMail

Using the Library

  • Collections overview
  • Borrow, renew, return
  • Connect from off campus
  • Interlibrary loan
  • Hours
  • Plan
  • Intranet (Staff Only)

Research Tools

  • EndNote
  • Grammarly
  • iThenticate
  • Mango Languages
  • Mendeley
  • Turnitin
  • Show more ..

Contact

  • Bilkent University
  • Main Campus Library
  • Phone: +90(312) 290-1298
  • Email: dspace@bilkent.edu.tr

Bilkent University Library © 2015-2025 BUIR

  • Privacy policy
  • Send Feedback