BacillusNet: An automated approach using RetinaNet for segmentation of pulmonary Tuberculosis bacillus-Reference-Cited by-同舟云学术

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BacillusNet: An automated approach using RetinaNet for segmentation of pulmonary Tuberculosis bacillus

Published:2021-09-05 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Symposium on Computers and Communications (ISCC)
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Author:

Dos Santos Reist Francisco Jose,Veloso Mateus Assis,Moraes Rodrigues Filipe Mateus,De Carvalho Brito Vitoria,Sales Dos Santos Patrick Ryan,Araujo Jose Denes Lima,De Andrade Lira Rabelo Ricardo,De Carvalho Filho Antonio Oseas

Funder

FAPEPI

CAPES

CNPq

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9631377/9631248/09631390.pdf?arnumber=9631390

Cited by 5 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. KochDet: BiFPN-based deep architecture for tuberculosis diagnosis;Biomedical Signal Processing and Control;2024-05

2. Detection and Prognosis of Pulmonary Tuberculosis Using ML Classifiers with Soft Computing;2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT);2024-02-09

3. A systematic review and repeatability study on the use of deep learning for classifying and detecting tuberculosis bacilli in microscopic images;Progress in Biophysics and Molecular Biology;2023-07

4. Research on detection method of Tubercle Bacilli based on the improved YOLOv5;Physics in Medicine & Biology;2023-05-05

5. Attention-driven RetinaNet for Parasitic Egg Detection;2022 IEEE International Symposium on Multimedia (ISM);2022-12

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