LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases
This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The proposed LDDNet was developed using additional layers...
Main Authors: | Prajoy Podder, Sanchita Rani Das, M. Rubaiyat Hossain Mondal, Subrato Bharati, Azra Maliha, Md Junayed Hasan, Farzin Piltan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-01-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/23/1/480 |
Similar Items
-
Rethinking Densely Connected Convolutional Networks for Diagnosing Infectious Diseases
by: Prajoy Podder, et al.
Published: (2023-05-01) -
Nutrients deficiency diagnosis of rice crop by weighted average ensemble learning
by: Md. Simul Hasan Talukder, et al.
Published: (2023-08-01) -
Deep Learning and Federated Learning for Screening COVID-19: A Review
by: M. Rubaiyat Hossain Mondal, et al.
Published: (2023-09-01) -
Development of Deep Learning with RDA U-Net Network for Bladder Cancer Segmentation
by: Ming-Chan Lee, et al.
Published: (2023-02-01) -
Diagnosis of Histopathological Images to Distinguish Types of Malignant Lymphomas Using Hybrid Techniques Based on Fusion Features
by: Zeyad Ghaleb Al-Mekhlafi, et al.
Published: (2022-09-01)