Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Unstructured grid generation
Download
035664.pdf
Date
1994
Author
Coşkun, Mehmet
Metadata
Show full item record
Item Usage Stats
170
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/9603
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Unstructured Textual Data Analysis for Underground Built Heritage (UBH) Knowledge Base
Karagöz, Pınar (CNR, 2021-01-01)
Unstructured Textual Data Analysis for Underground Built Heritage (UBH) Knowledge Base
Karagöz, Pınar (Consiglio Nazionale delle Ricerche (CNR), 2021-03-01)
Unstructured road recognition and following for mobile robots via image processing using Anns
Dilan, Rasim Aşkın; Koku, Ahmet Buğra; Department of Mechanical Engineering (2010)
For an autonomous outdoor mobile robot ability to detect roads existing around is a vital capability. Unstructured roads are among the toughest challenges for a mobile robot both in terms of detection and navigation. Even though mobile robots use various sensors to interact with their environment, being a comparatively low-cost and rich source of information, potential of cameras should be fully utilized. This research aims to systematically investigate the potential use of streaming camera images in detect...
Uninterruptable power supply a design approach.
Gündüz, Mustafa Asım; Department of Electrical Engineering (1978)
Unsupervised texture based image segmentation by simulated annealing using Markov random field and Potts models
Goktepe, M; Atalay, Mehmet Volkan; Yalabik, N; Yalabik, C (1998-01-01)
Unsupervised segmentation of images which are composed of various textures is investigated A coarse segmentation is achieved through a hierarchical self organizing map. This initial segmentation result is fed into a simulated annealing algorithm in which region and texture parameters are estimated using maximum likelihood technique. Region geometries are modeled as Potts model while textures are modeled as Markov random fields. Tests are performed an artificial textured images.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. Coşkun, “Unstructured grid generation,” Middle East Technical University, 1994.