Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
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
An intelligent Karyotyping architecture based on Artificial Neural Networks and features obtained by automated image analysis.
Date
1993
Author
Eskiizmililer, Selim
Metadata
Show full item record
Item Usage Stats
71
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/11854
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
An extensible mobile middleware architecture for reliable asynchronous messaging.
Ezbiderli, Mehmet Murat; Doğaç, Asuman; Department of Computer Engineering (2002)
An Intelligent vectorization tool.
Al-Ayyoub, Abdel-Elah; Tolun, Mehmet R; Department of Computer Engineering (1992)
An intelligent process planning system for prismatic parts using STEP features
Amaitik, Saleh M.; Kilic, S. Engin (Springer Science and Business Media LLC, 2007-01-01)
This paper presents an intelligent process planning system using STEP features (ST-FeatCAPP) for prismatic parts. The system maps a STEP AP224 XML data file, without using a complex feature recognition process, and produces the corresponding machining operations to generate the process plan and corresponding STEP-NC in XML format. It carries out several stages of process planning such as operations selection, tool selection, machining parameters determination, machine tools selection and setup planning. A h...
A Lightweight wireless multimedia sensor network architecture with object detection and classification capabilities
Civelek, Muhsin; Yazıcı, Adnan; Department of Computer Engineering (2017)
Use of wireless multimedia sensor networks (WMSNs) for surveillance applications has attracted the interest of many researchers. As with traditional sensor networks, it is easy to deploy and operate WMSNs. With inclusion of multimedia devices in wireless sensor networks (WSNs), it is possible to provide data to users that is more meaningful than that provided by scalar sensor-based systems alone; however, producing, storing, processing, analyzing, and transmitting multimedia data in sensor networks requires...
An Artificial Neural Network Based Pixel-by-Pixel Lossless Image Compression Method
Kamışlı, Fatih (2022-05-15)
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
S. Eskiizmililer, “An intelligent Karyotyping architecture based on Artificial Neural Networks and features obtained by automated image analysis.,” Middle East Technical University, 1993.