An Alternative Method for Cell Counting;
| dc.contributor.author | Özkan,A. | |
| dc.contributor.author | Belgin Işgör,S. | |
| dc.contributor.author | Tora,H. | |
| dc.contributor.author | Uyar,P. | |
| dc.contributor.author | Işcan,M. | |
| dc.date.accessioned | 2024-07-05T15:43:48Z | |
| dc.date.available | 2024-07-05T15:43:48Z | |
| dc.date.issued | 2011 | |
| dc.description.abstract | Cell counts and classification of the cells play an important role in the field of microbiology and cell biology. Although there exists many counting processes for cells of interest in suspension, the most basic cell counting process is performed by a person via the microscope. For counting cells the simplest, widely used and the most economic method is the use of hemocytometer counting. In this study, the hemocytometer counting was used but the the cells were counted by a proposed image based approach. The developed technique herein uses neural network along with the Hough transform. © 2011 IEEE. | en_US |
| dc.identifier.doi | 10.1109/SIU.2011.5929835 | |
| dc.identifier.isbn | 978-145770463-5 | |
| dc.identifier.scopus | 2-s2.0-79960396380 | |
| dc.identifier.uri | https://doi.org/10.1109/SIU.2011.5929835 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14411/3651 | |
| dc.language.iso | tr | en_US |
| dc.relation.ispartof | 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 -- 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 -- 20 April 2011 through 22 April 2011 -- Antalya -- 85528 | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | [No Keyword Available] | en_US |
| dc.title | An Alternative Method for Cell Counting; | en_US |
| dc.title.alternative | Hücre Sayimi İ̇çi̇n Alternati̇f Bi̇r Yöntem | en_US |
| dc.type | Conference Object | en_US |
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| gdc.description.department | Atılım University | en_US |
| gdc.description.departmenttemp | Özkan A., Elektrik ve Elektronik Mühendisliǧi Bölümü, ATILIM Üniversitesi, Turkey; Belgin Işgör S., Kimya Mühendisliǧi ve Uygulamali Kimya Bölümü, ATILIM Üniversitesi, Turkey; Tora H., Elektrik ve Elektronik Mühendisliǧi Bölümü, ATILIM Üniversitesi, Turkey; Uyar P., Biyolojik Bilimler Bölümü, ORTA DOǦU TEKNIK Üniversitesi, Turkey; Işcan M., Biyolojik Bilimler Bölümü, ORTA DOǦU TEKNIK Üniversitesi, Turkey | en_US |
| gdc.description.endpage | 1051 | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.startpage | 1048 | en_US |
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| gdc.oaire.keywords | Artificial Neural Network | |
| gdc.oaire.keywords | Signal processing | |
| gdc.oaire.keywords | Support vector machines | |
| gdc.oaire.keywords | Intelligent agents | |
| gdc.oaire.keywords | Pattern recognition techniques | |
| gdc.oaire.keywords | Classification technique | |
| gdc.oaire.keywords | Sensor units | |
| gdc.oaire.keywords | Tri-axial magnetometer | |
| gdc.oaire.keywords | Triaxial accelerometer | |
| gdc.oaire.keywords | Gaussian Mixture Model | |
| gdc.oaire.keywords | Naive Bayesian | |
| gdc.oaire.keywords | Comparative performance assessment | |
| gdc.oaire.keywords | Bayesian networks | |
| gdc.oaire.keywords | Differentiation rate | |
| gdc.oaire.keywords | Pattern recognition | |
| gdc.oaire.keywords | Human activities | |
| gdc.oaire.keywords | Magnetic sensors | |
| gdc.oaire.keywords | Accelerometers | |
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| gdc.virtual.author | Özkan, Akın | |
| gdc.virtual.author | Tora, Hakan | |
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