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DETECTION OF COVID-19 IN LOW ENERGY CHEST X-RAYS USING FAST R-CNN

Yıl 2022, Cilt: 4 Sayı: 1, 34 - 43, 26.04.2022

Öz

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.

Kaynakça

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Toplam 33 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Biyomedikal Mühendisliği
Bölüm Research Article
Yazarlar

Maryam Kareem Sakran Mamoori Bu kişi benim 0000-0002-0596-2546

Abdullahi Abdu Ibrahim Bu kişi benim 0000-0002-0596-2546

Yayımlanma Tarihi 26 Nisan 2022
Kabul Tarihi 26 Nisan 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 4 Sayı: 1

Kaynak Göster

APA 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), 34-43.