Pneumonia Detection from Pediatric Lung X-Ray Images with Convolutional Neural Network Method
BildiriAçık Erişim
Özet
Pneumonia can be cause diseases such as cough, fever and respiratory problems and to death in the progressive situations. Mostly lung x-ray images are used for diagnosis of pneumonia. In this study, an unique convolutional neural network model that can help experts in detection of pneumonia using lung x-ray images below 5 years of age. In the model, open access to 5840 images has been used, and various data increasing methods were used to increase the performance of the training and the success of the method. With the proposed convolutional neural network model, an accuracy rate of 94.55% has been achieved.
Anahtar Kelimeler
RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/16644Resmi atıflarda kullanılan kalıcı adresTam Kayıt
| Alan | Değer | Dil |
|---|---|---|
| dc.contributor.author | Demir, Yasin | |
| dc.contributor.author | Bingöl, Ozkan | |
| dc.contributor.other | IEEE | |
| dc.date.accessioned | 2026-10-22T10:32:50.172649063Z | |
| dc.date.available | 2026-10-22T10:32:50.172649063Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Pneumonia can be cause diseases such as cough, fever and respiratory problems and to death in the progressive situations. Mostly lung x-ray images are used for diagnosis of pneumonia. In this study, an unique convolutional neural network model that can help experts in detection of pneumonia using lung x-ray images below 5 years of age. In the model, open access to 5840 images has been used, and various data increasing methods were used to increase the performance of the training and the success of the method. With the proposed convolutional neural network model, an accuracy rate of 94.55% has been achieved. | |
| dc.identifier.doi | 10.1109/siu53274.2021.9477835 | |
| dc.identifier.isbn | 978-1-6654-3649-6 | |
| dc.identifier.uri | https://rdlopen.rawdatalibrary.net/r/gumushane/16644 | |
| dc.identifier.wos | WOS:000808100700078 | |
| dc.language.iso | tr | |
| dc.publisher | IEEE | |
| dc.relation.conference | 29th IEEE Conference on Signal Processing and Communications Applications (SIU) | |
| dc.relation.ispartof | 29TH IEEE CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS (SIU 2021) | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Lung X-ray images | |
| dc.subject | deep learning | |
| dc.subject | convolutional neural network | |
| dc.subject | pneumonia | |
| dc.subject | pediatric | |
| dc.subject.classification | Engineering, Electrical & Electronic | |
| dc.subject.classification | Telecommunications | |
| dc.subject.classification | Engineering | |
| dc.title | Pneumonia Detection from Pediatric Lung X-Ray Images with Convolutional Neural Network Method | |
| dc.type | Conference Object | |
| dspace.entity.type | Publication | |
| rdl.citation.openalex | 3 | |
| rdl.citation.wos | 2 | |
| rdl.conference.date | JUN 09-11, 2021 | |
| rdl.conference.place | ELECTR NETWORK | |
| rdl.oa.status | closed | |
| rdl.oa.status | green | |
| rdl.oa.url | https://hdl.handle.net/20.500.12440/5800 | |
| rdl.sdg | SDG03 | |
| rdl.source.index | WOS | |
| rdl.wos.index | Conference Proceedings Citation Index - Science (CPCI-S) |

