An Improved Densenet Deep Neural Network Model for Tuberculosis Detection Using Chest X-Ray Images

Author:

Huy Vo Trong Quang1,Lin Chih-Min1ORCID

Affiliation:

1. Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan

Funder

Ministry of Science and Technology of Republic of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Cited by 22 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Performance Analysis on Various Tuberculosis Detection Techniques and Remedial Suggestions Using Deep Learning;2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS);2024-07-10

2. Analysing the Performance of Dense Net in the context of Tuberculosis Disease;2024 International Conference on Advancements in Power, Communication and Intelligent Systems (APCI);2024-06-21

3. TSSG-CNN: A Tuberculosis Semantic Segmentation-Guided Model for Detecting and Diagnosis Using the Adaptive Convolutional Neural Network;Diagnostics;2024-06-01

4. An Effective Identification of Tuberculosis in Chest X-rays Using Convolutional Neural Network Model;2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT);2024-05-02

5. From Pixels to Diagnosis: Convolutional Neural Networks in Tuberculosis Screening;2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT);2024-05-02

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