Detection of covid-19 in low energy chest x-rays using fast R-CNN
Yükleniyor...
Dosyalar
Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Altınbaş Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In recent years, it has been shown that deep learning can produce similar performance increases
in the domain of medical image analysis for object detection and segmentation tasks. Notable recent
work includes important medical applications, for example, in the field of pulmonology (classification
of lung diseases and detection of pulmonary nodules on CT images in this paper, we present a variation
of CNNs, which works extremely well on a current data set — a customized architecture with optimal
parameters. In our contribution, we focus on lowering the complexity of our network, while yet reaching
a phenomenally high degree of accuracy. To achieve this aim, our model has been tailored for high
performance and an easy design.
Açıklama
Anahtar Kelimeler
Component, Formatting, Style, Styling, Insert
Kaynak
AURUM Journal of Health Sciences
WoS Q Değeri
Scopus Q Değeri
Cilt
4
Sayı
1
Künye
Mamoori, M. K. S.,Ibrahim, A. A. (2022). Detection of covid-19 in low energy chest x-rays using fast R-CNN. AURUM Journal of Health Sciences, 4(1), 35-43.
