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Saichon Jaiyen. Automated ensemble deep learning for chest X-ray Covid-19 image classification using multiple hyperparameter optimizations. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2023.
Automated ensemble deep learning for chest X-ray Covid-19 image classification using multiple hyperparameter optimizations
Name: Mudaser, Muhibullah
Organization :
King Mongkut's University of Technology Thonburi. School of Information Technology
Email :
mahibullah.mudaser123@gmail.com
Name: Worarat Krathu
Organization :
King Mongkut's University of Technology Thonburi. School of Information Technology
Email :
worarat.kra@sit.kmutt.ac.th
Name: Saichon Jaiyen
Organization :
King Mongkut's University of Technology Thonburi. School of Information Technology
Email :
saichon.jai@sit.kmutt.ac.th
keyword:
BayesSearchCV
Abstract:
The COVID-19 pandemic has created an urgent
need for reliable methods to detect the virus. Chest X-ray images
have emerged as a valuable diagnostic tool due to their
accessibility and potential for identifying COVID-19 patterns. A
review of the existing literature in this area reveals a gap in the
research related to the use of automated ensemble deep learning
techniques for Covid-19 image classification, particularly in the
context of hyperparameter optimization. Therefore, the current
study seeks to fill this research gap by conducting experiments
to determine the effectiveness of various ensemble deep-learning
approaches and exploring the impact of multiple
hyperparameter optimizations on the accuracy of the
classification model. The methodology involves collecting a large
dataset of COVID and normal chest X-ray images,
preprocessing the data, and developing individual deep-learning
models such as DenseNet201, DenseNet121, and MobileNetV2.
Hyperparameter optimization techniques, including
BayesSearchCV, GridSearchCV, and RandomSearchCV, are
applied to fine-tune the models. The results demonstrate high
accuracy, specificity, and sensitivity values for the selected
models. Ensemble method used, such as stacking effectively
combined the strengths of different models, achieved results an
accuracy of 95.98%, sensitivity of 95.39%, and specificity of
96.57%.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2023
Modified:
2024-04-23
Issued:
2024-04-23
บทความ/Article
application/pdf
BibliograpyCitation :
In Institute of Electrical and Electronics Engineers. The 27th International Computer Science and Engineering Conference 2023 (ICSEC 2023) (pp.348-353). Bangkok : Institute of Electrical and Electronics Engineers
eng
©copyrights King Mongkut's University of Technology North Bangkok
RightsAccess:
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0.032175 วินาที
Mudaser, Muhibullah
| Title | Contributor | Type |
|---|---|---|
| Automated ensemble deep learning for chest X-ray Covid-19 image classification using multiple hyperparameter optimizations
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Mudaser, Muhibullah;Worarat Krathu;Saichon Jaiyen | บทความ/Article |
Worarat Krathu
| Title | Contributor | Type |
|---|---|---|
| Automated ensemble deep learning for chest X-ray Covid-19 image classification using multiple hyperparameter optimizations
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Mudaser, Muhibullah;Worarat Krathu;Saichon Jaiyen | บทความ/Article |
Saichon Jaiyen
| Title | Contributor | Type |
|---|---|---|
| Automated ensemble deep learning for chest X-ray Covid-19 image classification using multiple hyperparameter optimizations
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Mudaser, Muhibullah;Worarat Krathu;Saichon Jaiyen | บทความ/Article | |
| Comparing and normalizing the measurement of step counts and heart rates of selected wristbands and smartwatches
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