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Original Article
Attention-Driven Pneumonia Detection in Chest X-Rays with Threshold-Optimized EfficientNetB0–CBAM
Shalini Baghel1
Shanu Kuttan Rakesh2
1 2 Department of Computer Science & Engineering, Chouksey Engineering College, Bilaspur (CSVTU Bhilai), Chhattisgarh, India.
Published Online: May-June 2026
Pages: 374-382
Cite this article
↗ https://www.doi.org/10.59256/ijire.20260703041
References
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2591–2603, 2024. DOI: 10.52783/jes.2591
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Springer Conf., 2024. DOI: 10.1007/978-981-99-9637-7_37
10. Y. Fu, P. Xue, Z. Zhang, and E. Dong, "PKA2-Net: Prior Knowledge-Based Active Attention Network for Accurate Pneumonia
Diagnosis on Chest X-Ray Images," IEEE J. Biomed. Health Inform., vol. 27, no. 8, pp. 4004–4015, 2023. DOI:
10.1109/JBHI.2023.3267057
11. A. Sharma, S. Verma, P. Priyanka, A. Verma, and N. Duhan, "Attention-Enhanced CBAM-VGG-16 for Optimized Pneumonia
Detection in Chest X-Ray Imaging," in Proc. IEEE Int. Conf. Cloud Eng. (IC2E), 2025. DOI: 10.1109/ic2e365635.2025.11167569
12. M. Yerzhanuly, "LungX: A Hybrid EfficientNet-Vision Transformer Architecture with Multi-Scale Attention for Accurate Pneumonia
Detection," arXiv preprint arXiv:2511.18425, 2025. DOI: 10.48550/arxiv.2511.18425
13. Y. Song, H. Ren, F. Jing, C. He, and Y. Xie, "Enhancing Pneumonia Diagnosis Using a Ensemble Transformer-Based Attention
Network for Chest X-Ray Image Analysis," in Proc. IEEE Int. Conf. Big Data Process. Comput. (BDPC), 2024. DOI:
10.1109/bdpc59998.2024.10649346
14. S.-M. Cha, S.-S. Lee, and B. Ko, "Attention-Based Transfer Learning for Efficient Pneumonia Detection in Chest X-ray Images,"
Appl. Sci., vol. 11, no. 3, p. 1242, 2021. DOI: 10.3390/APP1103124215. Z. Guo, J. Zhang, Y. Zuo, P. Liu, and R. Tang, "Channel Attention Residual Network for Diagnosing Pneumonia," in Proc. IEEE Int.
Conf. Artif. Intell. Big Data (ICAIBD), 2021. DOI: 10.1109/ICAIBD51990.2021.9459102
16. T. T. Mac, X. T. Nguyen, H. A. Bui, T.-H. Nguyen, and H. H. Ly, "An Attention-Enhanced Hybrid Deep Learning Model Based on
VGG16 and VGG19 for Pneumonia Detection from Chest X-ray Images," Int. J. Online Eng., vol. 21, no. 12, pp. 55953, 2025. DOI:
10.3991/ijoe.v21i12.55953
17. A. M. Ahmed, G. A. Babikir, and S. M. Osman, "Classification of Pneumonia Using Deep Convolutional Neural Network," Am. J.
Comput. Sci. Technol., vol. 5, no. 2, pp. 11–20, 2022. DOI: 10.11648/j.ajcst.20220502.11
18. A. Roy, A. Bhattacharjee, D. Oliva, O. Ramos-Soto, and F. J. A. Padilla, "FA-Net: A Fuzzy Attention-aided Deep Neural Network for
Pneumonia Detection in Chest X-Rays," arXiv preprint arXiv:2406.15117, 2024. DOI: 10.48550/arxiv.2406.15117
19. S. Shrimali, "Optimizing Chest X-ray Analysis for Pneumonia Detection Through Comparative Evaluation of Transfer Learning CNN
Architectures," in Proc. IEEE Int. Conf. Innov. Comput. Technol. (I2CT), 2024. DOI: 10.1109/i2ct61223.2024.10543957
20. S. Aljawarneh and R. Al-Quraan, "Pneumonia Detection Using Enhanced Convolutional Neural Network Model on Chest X-Ray
Images," Big Data, vol. 11, no. 4, pp. 261–275, 2023. DOI: 10.1089/big.2022.0261
21. S. Kashyap, H. N. Patel, and Y. R. Kumar, "Hybrid Deep Learning and Machine Learning Framework for Automated Pneumonia
Detection in Chest X-ray Images," MethodsX, vol. 12, p. 103729, 2025. DOI: 10.1016/j.mex.2025.103729
22. N. Waisi, "Comparative Evaluation of ResNet-50 and EfficientNet-B1 for Pneumonia Detection in Chest X-Ray Images Using Transfer
Learning," Int. J. Comput. Electron. Aspects Eng., vol. 6, no. 2, pp. 20250405, 2025. DOI: 10.26706/ijceae.6.2.20250405
23. M. Nahiduzzaman, M. O. F. Goni, M. S. Anower, M. R. Islam, and M. Ahsan, "A Novel Method for Multivariant Pneumonia
Classification Based on Hybrid CNN-PCA Based Feature Extraction Using Extreme Learning Machine With CXR Images," IEEE
Access, vol. 9, pp. 147975–147991, 2021. DOI: 10.1109/ACCESS.2021.3123782
24. S. Goyal and R. Singh, "Detection and Classification of Lung Diseases for Pneumonia and Covid-19 Using Machine and Deep Learning
Techniques," J. Ambient Intell. Humanized Comput., vol. 12, pp. 1–16, 2021. DOI: 10.1007/S12652-021-03464-7
25. K. Kc, Z. Yin, M. Wu, and Z. Wu, "Evaluation of Deep Learning-Based Approaches for COVID-19 Classification Based on Chest X-
ray Images," Signal Image Video Process., vol. 15, pp. 959–967, 2021. DOI: 10.1007/S11760-020-01820-2
26. M. Tan and Q. V. Le, "EfficientNet: Rethinking model scaling for convolutional neural networks," in Proc. Int. Conf. Mach. Learn.
(ICML), 2019, pp. 6105–6114.
27. S. Woo, J. Park, J.-Y. Lee, and I. S. Kweon, "CBAM: Convolutional block attention module," in Proc. Eur. Conf. Comput. Vis.
(ECCV), 2018, pp. 3–19.
28. D. S. Kermany et al., "Identifying medical diagnoses and treatable diseases by image-based deep learning," Cell, vol. 172, no. 5, pp.
1122–1131, 2018. DOI: 10.1016/j.cell.2018.02.010
29. K. Simonyan and A. Zisserman, "Very deep convolutional networks for large-scale image recognition," in Proc. Int. Conf. Learn.
Represent. (ICLR), 2015. arXiv:1409.1556
30. K. He, X. Zhang, S. Ren, and J. Sun, "Deep residual learning for image recognition," in Proc. IEEE Conf. Comput. Vis. Pattern
Recognit. (CVPR), 2016, pp. 770–778.
31. G. Huang, Z. Liu, L. van der Maaten, and K. Q. Weinberger, "Densely connected convolutional networks," in Proc. IEEE Conf.
Comput. Vis. Pattern Recognit. (CVPR), 2017, pp. 4700–4708.
32. D. P. Kingma and J. Ba, "Adam: A method for stochastic optimization," in Proc. Int. Conf. Learn. Represent. (ICLR), 2015.
arXiv:1412.6980
33. P. Rajpurkar et al., "CheXNet: Radiologist-level pneumonia detection on chest X-rays with deep learning," arXiv:1711.05225, 2017.
34. J. Hu, L. Shen, and G. Sun, "Squeeze-and-excitation networks," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), 2018,
pp. 7132–7141.
Neural Network Based on Two Parallel Visual Geometry Group Architectures and Machine Learning Classifiers," IEEE Access, vol.
10, pp. 62915–62932, 2022. DOI: 10.1109/access.2022.3182498
2. S. Y. Prasetyo, "CBAM-Enhanced Classification Head for VGG16-Based Pneumonia Detection," in Proc. IEEE Int. Conf. Informatics,
Comput., Sci. (ICICOS), 2025. DOI: 10.1109/icicos68590.2025.11329868
3. K. B. Lolong and P. A. Suri, "Pneumonia Classification and Detection from Chest X-Ray Images Using Transfer Learning," in Proc.
IEEE Int. Conf. Oper. Res. Inf. Syst. (ICORIS), 2025. DOI: 10.1109/icoris67789.2025.11296118
4. Z. Zhou, Y. Liu, Q. Wang, and T. T. Toe, "Detection of Pneumonia Based on ResNet Improved by Attention Mechanism," in Proc.
IEEE Int. Conf. Power Energy Convers. Appl. (ICPECA), 2023. DOI: 10.1109/ICPECA56706.2023.10076216
5. O. M. El Zein, M. M. Soliman, A. Elkholy, and N. I. Ghali, "Transfer Learning Based Model for Pneumonia Detection in Chest X-ray
Images," Int. J. Intell. Eng. Syst., vol. 14, no. 5, pp. 66–79, 2021. DOI: 10.22266/IJIES2021.1031.06
6. Q. An, W. Chen, and W. Shao, "A Deep Convolutional Neural Network for Pneumonia Detection in X-ray Images with Attention
Ensemble," Diagnostics, vol. 14, no. 4, p. 390, 2024. DOI: 10.3390/diagnostics14040390
7. R. P. Díaz, A. Dahou, M. A. Elaziz, and M. Kayed, "Pneumonia Detection on Chest X-ray Images Using Ensemble of Deep
Convolutional Neural Networks," arXiv preprint arXiv:2312.07965, 2023. DOI: 10.48550/arxiv.2312.07965
8. R. D. Shirwaikar, V. Anitha, V. S. Rao, and A. K. Kaushal, "A Machine Learning Application for Medical Image Analysis Using Deep
Convolutional Neural Networks (CNNs) and Transfer Learning Models for Pneumonia Detection," J. Electr. Syst., vol. 20, no. 3, pp.
2591–2603, 2024. DOI: 10.52783/jes.2591
9. J. Zhang and B. Zhang, "Auxiliary Diagnosis of Pneumonia Based on Convolutional Attention and Parameter Migration," in Proc.
Springer Conf., 2024. DOI: 10.1007/978-981-99-9637-7_37
10. Y. Fu, P. Xue, Z. Zhang, and E. Dong, "PKA2-Net: Prior Knowledge-Based Active Attention Network for Accurate Pneumonia
Diagnosis on Chest X-Ray Images," IEEE J. Biomed. Health Inform., vol. 27, no. 8, pp. 4004–4015, 2023. DOI:
10.1109/JBHI.2023.3267057
11. A. Sharma, S. Verma, P. Priyanka, A. Verma, and N. Duhan, "Attention-Enhanced CBAM-VGG-16 for Optimized Pneumonia
Detection in Chest X-Ray Imaging," in Proc. IEEE Int. Conf. Cloud Eng. (IC2E), 2025. DOI: 10.1109/ic2e365635.2025.11167569
12. M. Yerzhanuly, "LungX: A Hybrid EfficientNet-Vision Transformer Architecture with Multi-Scale Attention for Accurate Pneumonia
Detection," arXiv preprint arXiv:2511.18425, 2025. DOI: 10.48550/arxiv.2511.18425
13. Y. Song, H. Ren, F. Jing, C. He, and Y. Xie, "Enhancing Pneumonia Diagnosis Using a Ensemble Transformer-Based Attention
Network for Chest X-Ray Image Analysis," in Proc. IEEE Int. Conf. Big Data Process. Comput. (BDPC), 2024. DOI:
10.1109/bdpc59998.2024.10649346
14. S.-M. Cha, S.-S. Lee, and B. Ko, "Attention-Based Transfer Learning for Efficient Pneumonia Detection in Chest X-ray Images,"
Appl. Sci., vol. 11, no. 3, p. 1242, 2021. DOI: 10.3390/APP1103124215. Z. Guo, J. Zhang, Y. Zuo, P. Liu, and R. Tang, "Channel Attention Residual Network for Diagnosing Pneumonia," in Proc. IEEE Int.
Conf. Artif. Intell. Big Data (ICAIBD), 2021. DOI: 10.1109/ICAIBD51990.2021.9459102
16. T. T. Mac, X. T. Nguyen, H. A. Bui, T.-H. Nguyen, and H. H. Ly, "An Attention-Enhanced Hybrid Deep Learning Model Based on
VGG16 and VGG19 for Pneumonia Detection from Chest X-ray Images," Int. J. Online Eng., vol. 21, no. 12, pp. 55953, 2025. DOI:
10.3991/ijoe.v21i12.55953
17. A. M. Ahmed, G. A. Babikir, and S. M. Osman, "Classification of Pneumonia Using Deep Convolutional Neural Network," Am. J.
Comput. Sci. Technol., vol. 5, no. 2, pp. 11–20, 2022. DOI: 10.11648/j.ajcst.20220502.11
18. A. Roy, A. Bhattacharjee, D. Oliva, O. Ramos-Soto, and F. J. A. Padilla, "FA-Net: A Fuzzy Attention-aided Deep Neural Network for
Pneumonia Detection in Chest X-Rays," arXiv preprint arXiv:2406.15117, 2024. DOI: 10.48550/arxiv.2406.15117
19. S. Shrimali, "Optimizing Chest X-ray Analysis for Pneumonia Detection Through Comparative Evaluation of Transfer Learning CNN
Architectures," in Proc. IEEE Int. Conf. Innov. Comput. Technol. (I2CT), 2024. DOI: 10.1109/i2ct61223.2024.10543957
20. S. Aljawarneh and R. Al-Quraan, "Pneumonia Detection Using Enhanced Convolutional Neural Network Model on Chest X-Ray
Images," Big Data, vol. 11, no. 4, pp. 261–275, 2023. DOI: 10.1089/big.2022.0261
21. S. Kashyap, H. N. Patel, and Y. R. Kumar, "Hybrid Deep Learning and Machine Learning Framework for Automated Pneumonia
Detection in Chest X-ray Images," MethodsX, vol. 12, p. 103729, 2025. DOI: 10.1016/j.mex.2025.103729
22. N. Waisi, "Comparative Evaluation of ResNet-50 and EfficientNet-B1 for Pneumonia Detection in Chest X-Ray Images Using Transfer
Learning," Int. J. Comput. Electron. Aspects Eng., vol. 6, no. 2, pp. 20250405, 2025. DOI: 10.26706/ijceae.6.2.20250405
23. M. Nahiduzzaman, M. O. F. Goni, M. S. Anower, M. R. Islam, and M. Ahsan, "A Novel Method for Multivariant Pneumonia
Classification Based on Hybrid CNN-PCA Based Feature Extraction Using Extreme Learning Machine With CXR Images," IEEE
Access, vol. 9, pp. 147975–147991, 2021. DOI: 10.1109/ACCESS.2021.3123782
24. S. Goyal and R. Singh, "Detection and Classification of Lung Diseases for Pneumonia and Covid-19 Using Machine and Deep Learning
Techniques," J. Ambient Intell. Humanized Comput., vol. 12, pp. 1–16, 2021. DOI: 10.1007/S12652-021-03464-7
25. K. Kc, Z. Yin, M. Wu, and Z. Wu, "Evaluation of Deep Learning-Based Approaches for COVID-19 Classification Based on Chest X-
ray Images," Signal Image Video Process., vol. 15, pp. 959–967, 2021. DOI: 10.1007/S11760-020-01820-2
26. M. Tan and Q. V. Le, "EfficientNet: Rethinking model scaling for convolutional neural networks," in Proc. Int. Conf. Mach. Learn.
(ICML), 2019, pp. 6105–6114.
27. S. Woo, J. Park, J.-Y. Lee, and I. S. Kweon, "CBAM: Convolutional block attention module," in Proc. Eur. Conf. Comput. Vis.
(ECCV), 2018, pp. 3–19.
28. D. S. Kermany et al., "Identifying medical diagnoses and treatable diseases by image-based deep learning," Cell, vol. 172, no. 5, pp.
1122–1131, 2018. DOI: 10.1016/j.cell.2018.02.010
29. K. Simonyan and A. Zisserman, "Very deep convolutional networks for large-scale image recognition," in Proc. Int. Conf. Learn.
Represent. (ICLR), 2015. arXiv:1409.1556
30. K. He, X. Zhang, S. Ren, and J. Sun, "Deep residual learning for image recognition," in Proc. IEEE Conf. Comput. Vis. Pattern
Recognit. (CVPR), 2016, pp. 770–778.
31. G. Huang, Z. Liu, L. van der Maaten, and K. Q. Weinberger, "Densely connected convolutional networks," in Proc. IEEE Conf.
Comput. Vis. Pattern Recognit. (CVPR), 2017, pp. 4700–4708.
32. D. P. Kingma and J. Ba, "Adam: A method for stochastic optimization," in Proc. Int. Conf. Learn. Represent. (ICLR), 2015.
arXiv:1412.6980
33. P. Rajpurkar et al., "CheXNet: Radiologist-level pneumonia detection on chest X-rays with deep learning," arXiv:1711.05225, 2017.
34. J. Hu, L. Shen, and G. Sun, "Squeeze-and-excitation networks," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), 2018,
pp. 7132–7141.
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