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
Evre uyumlu uzak ve yakın alan kaynakların konum kestirimi için seyrek işaret geri oluşturma
Date
2015-05-16
Author
Tuncer, Temel Engin
Metadata
Show full item record
Item Usage Stats
69
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/84385
Collections
Unverified, Conference / Seminar
Suggestions
OpenMETU
Core
Use of the ambiguity function technique for target detection in phase coded continuous wave radars
Çankaya, Erkan; Sayan, Gönül; Department of Electrical and Electronics Engineering (2005)
The goal of this thesis study is to investigate the Ambiguity Function Technique for target detection in phase-coded continuous wave radar. Also, phase shift keying techniques are examined in detail. Continuous Wave (CW) Radars, which are also known as Low Probability of Intercept (LPI) radars, emit continuous signals in time which are modulated by either frequency modulation or phase modulation techniques. Modulation of the transmitted radar signal is needed to estimate both the range and the radial veloci...
Convolutional neural network based brain MRI segmentation
Baydar, Bora; Akar, Gözde; Department of Electrical and Electronics Engineering (2018)
Visualization of the inner parts of human body is crucial in modern medicine and magnetic resonance imaging(MRI) is one of the widely used medical imaging methods. Manual analysis of MRIs, however, wastes the valuable time of experts. Development of an automatic segmentation method for brain MRIs can save time spent by the experts and can avoid human error factor. In this thesis, convolutional neural network (CNN) based methods are applied on brain MRI segmentation problem. The basic architectures used are ...
Quality Enhancement of Computed Tomography Images of Porous Media Using Convolutional Neural Networks
Yıldırım, Ertuğrul Umut; Uğur, Ömür; Glatz, Guenther; Department of Scientific Computing (2022-2-11)
Computed tomography has been widely used in clinical and industrial applications as a non-destructive visualization technology. The quality of computed tomography scans has a strong effect on the accuracy of the estimated physical properties of the investigated sample. X-ray exposure time is a crucial factor for scan quality. Ideally, long exposure time scans, yielding large signal-to-noise ratios, are available if physical properties are to be delineated. However, especially in micro-computed tomography ap...
Çevre İktidar ve Siyaset Yeşil Bir Tarihsel Ekolojinin Sınırları
Dursun, Selçuk (2012-04-06)
Person Re-identification Using Convolutional Neural Networks
Aksu, Fatih; Direkoğlu, Cem; Electrical and Electronics Engineering (2021-9-6)
Person re-identification is an important computer vision topic particularly for surveillance system applications. The main aim of person re-identification is to identify previously observed individuals over a camera network with nonoverlapping occurrences. Various approaches have been introduced to overcome this problem. This study has two distinct key contributions. First, a new part-based method for person re-identification, which combines semantically partitioned body part masks with a convolutional neur...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
T. E. Tuncer, “Evre uyumlu uzak ve yakın alan kaynakların konum kestirimi için seyrek işaret geri oluşturma,” 2015, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/84385.