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Original Article
Comparative Performance Evaluation of VGG-19 and ResNet-50 on Brain MRI Images
Vikas Arora1
Deepak Kumar2
Abhinav Pratap Soni3
Mohd Farman Sajjad4
Anurag Agarwal5
1 2 3 4 5 Department of Computer Science & Engineering, Roorkee Institute of Technology, Uttarakhand, India.
Published Online: November-December 2025
Pages: 25-31
Cite this article
↗ https://www.doi.org/10.59256/ijsreat.20250506004
References
1. K. Priyadharshini, P. Krishnamoorthy, B. S. Ganapathy, K. Karthikeyan, U. Maheswari, and R. Peddaveni, “Artificial Intelligence Assisted Improved Design to Predict Brain Tumor on Earlier Stages using Deep Learning Principle,” in Proc. 2023 IEEE AICERA/ICIS, 2023, pp. 1–6, doi: 10.1109/AICERA/ICIS59538.2023.10420011.
2. V. Konde, S. Shyam, P. Ayush, S. Suchitra, and T. Kalita, “Brain Tumor Detection Based on Deep Learning Neural Network Using MRI,” in Proc. 2024 IEEE ADICS, 2024, pp. 1–7, doi: 10.1109/ADICS58448.2024.10533532.
3. M. C. S. Tang and S. S. Teoh, “Brain Tumor Detection from MRI Images Based on ResNet18,” in Proc. 2023 IEEE ISCON, 2023, pp. 1–5, doi: 10.1109/ISCON57294.2023.10112025.
4. A. S. Jadhav, R. Pawar, S. M. Hattaraki, S. Bagali, R. S. Patil, and B. Patil, “Brain Tumor Detection Using MRI Image Processing Techniques,” in Proc. 2024 IEEE INNOVA, 2024, pp. 1–6, doi: 10.1109/INNOVA63080.2024.10846990.
5. S. Koshti, V. Degaonkar, I. Modi, I. Srivastava, J. Panambor, and A. Jagtap, “Brain Tumor Detection System using Convolutional Neural Network,” in Proc. 2022 IEEE PuneCon, 2022, pp. 1–5, doi: 10.1109/PUNECON55413.2022.10014714.
6. M. Menagadevi, S. Sharmila, D. Thiyagarajan, N. Madian, and S. Devaraj, “Brain Tumor Detection Using VGG16 and EfficientNet B3 Model,” in Proc. 2024 IEEE ICACCS, 2024, pp. 1–6, doi: 10.1109/ICACCS60874.2024.10717050.
7. D. B., G. S., S. S., S. B., and Y. M., “Brain Tumor Detection with Severity Identification Using K-Means Clustering,” in Proc. 2025 IEEE CE2CT, 2025, pp. 1–6, doi: 10.1109/CE2CT64011.2025.10939308.
8. A. Sharma, N. Agarwal, R. Rathore, A. Arora, and S. Gupta, “Advancements in Brain Tumor Detection Utilizing Xception Enhanced Tumor Identifier Network,” in Proc. 2024 IEEE Conference on Computing, Communication and Intelligent Systems (ICCCIS), 2024, pp. 1–6, doi: 10.1109/ICCCIS57492.2024.11122331.
9. S. Saradha, S. C. S. Krishna, S. G. Ramanathan, N. Ilamugunthan, and S. Kavin, "Brain Tumour Detection using Deep Learning - A Comprehensive Study," in 2024 10th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2024, pp. 1465-1467, doi: 10.1109/ICACCS60874.2024.10717236.
10. J. K. Periasamy, S. Buvana, and P. Jeevitha, "Comparison of VGG-19 and RESNET-50 Algorithms in Brain Tumor Detection," in 2023 IEEE 8th International Conference for Convergence in Technology (I2CT), Pune, India, Apr. 2023, pp. 1–6, doi: 10.1109/I2CT57861.2023.10126451.
11. J. Ramasamy, R. Doshi, and K. K. Hiran, "Detection of Brain Tumor in Medical Images Based on Feature Extraction by HOG and Machine Learning Algorithms," 2022 International Conference on Trends in Quantum Computing and Emerging Business Technologies (TQCEBT),
Pune, India, Oct. 2022, pp. 1–5, doi: 10.1109/TQCEBT54229.2022.10041564.
12. J. Akonda, S. T. Alvi, C. A. A. Era, S. J. Mitu, and M. N. Uddin, “MRI Based Brain Tumor Detection Comprising a Hybrid Segmentation Technique,” 2024 Int. Conf. on Decision Aid Sciences and Applications (DASA), pp. 1–6, doi:10.1109/DASA63652.2024.10836563.
13. S. Parvathavarthini, D. V. S, K. N. S, and S. R, “Integrating YOLOV8 and Grad-CAM++ for Enhanced Brain Tumor Detection and Interpretation,” Proc. Int. Conf. on Inventive Computation Technologies (ICICT-2025), pp. 530–535, doi:10.1109/ICICT64420.2025.11004921.
14. M. V. M. Thota and B. R. Prasad, “INCS: A Novel Brain Tumor Detection Methodology Design Based on Deep Learning Assisted Intelligent Neural Classification Strategy,” 2024 Int. Conf. on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSESES), pp. 1–6, doi:10.1109/ICSES63760.2024.10910369.
15. N. Al-Ani and O. Al-Shamma, “Implementing a Novel Low Complexity CNN Model for Brain Tumor Detection,” 2022 8th Int. Conf. on Contemporary Information Technology and Mathematics (ICCITM), pp. 358–359, doi:10.1109/ICCITM56309.2022.10031630.
16. S. Desai and M. Mushrif, “Early Detection of Brain Tumor using ResNet50 and Transfer Learning,” 2024 3rd Int. Conf. on Automation, Computing and Renewable Systems (ICACRS), pp. 1488–1493, doi:10.1109/ICACRS62842.2024.10841701.
17. S. P. N, B. S, K. K. N, and P. A. Vijaya, “Detection of Human Brain Tumors Using an UWB Patch Antenna at 28GHz,” 2023 Int. Conf. on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), pp. 1–8, doi:10.1109/IITCEE57236.2023.10090949.
18. J. K. Periasamy, B. S, and J. P, “Comparison of VGG-19 and RESNET-50 Algorithms in Brain Tumor Detection,” 2023 IEEE 8th Int. Conf. for Convergence in Technology (I2CT), pp. 1–6, doi:10.1109/I2CT57861.2023.10126451.
2. V. Konde, S. Shyam, P. Ayush, S. Suchitra, and T. Kalita, “Brain Tumor Detection Based on Deep Learning Neural Network Using MRI,” in Proc. 2024 IEEE ADICS, 2024, pp. 1–7, doi: 10.1109/ADICS58448.2024.10533532.
3. M. C. S. Tang and S. S. Teoh, “Brain Tumor Detection from MRI Images Based on ResNet18,” in Proc. 2023 IEEE ISCON, 2023, pp. 1–5, doi: 10.1109/ISCON57294.2023.10112025.
4. A. S. Jadhav, R. Pawar, S. M. Hattaraki, S. Bagali, R. S. Patil, and B. Patil, “Brain Tumor Detection Using MRI Image Processing Techniques,” in Proc. 2024 IEEE INNOVA, 2024, pp. 1–6, doi: 10.1109/INNOVA63080.2024.10846990.
5. S. Koshti, V. Degaonkar, I. Modi, I. Srivastava, J. Panambor, and A. Jagtap, “Brain Tumor Detection System using Convolutional Neural Network,” in Proc. 2022 IEEE PuneCon, 2022, pp. 1–5, doi: 10.1109/PUNECON55413.2022.10014714.
6. M. Menagadevi, S. Sharmila, D. Thiyagarajan, N. Madian, and S. Devaraj, “Brain Tumor Detection Using VGG16 and EfficientNet B3 Model,” in Proc. 2024 IEEE ICACCS, 2024, pp. 1–6, doi: 10.1109/ICACCS60874.2024.10717050.
7. D. B., G. S., S. S., S. B., and Y. M., “Brain Tumor Detection with Severity Identification Using K-Means Clustering,” in Proc. 2025 IEEE CE2CT, 2025, pp. 1–6, doi: 10.1109/CE2CT64011.2025.10939308.
8. A. Sharma, N. Agarwal, R. Rathore, A. Arora, and S. Gupta, “Advancements in Brain Tumor Detection Utilizing Xception Enhanced Tumor Identifier Network,” in Proc. 2024 IEEE Conference on Computing, Communication and Intelligent Systems (ICCCIS), 2024, pp. 1–6, doi: 10.1109/ICCCIS57492.2024.11122331.
9. S. Saradha, S. C. S. Krishna, S. G. Ramanathan, N. Ilamugunthan, and S. Kavin, "Brain Tumour Detection using Deep Learning - A Comprehensive Study," in 2024 10th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2024, pp. 1465-1467, doi: 10.1109/ICACCS60874.2024.10717236.
10. J. K. Periasamy, S. Buvana, and P. Jeevitha, "Comparison of VGG-19 and RESNET-50 Algorithms in Brain Tumor Detection," in 2023 IEEE 8th International Conference for Convergence in Technology (I2CT), Pune, India, Apr. 2023, pp. 1–6, doi: 10.1109/I2CT57861.2023.10126451.
11. J. Ramasamy, R. Doshi, and K. K. Hiran, "Detection of Brain Tumor in Medical Images Based on Feature Extraction by HOG and Machine Learning Algorithms," 2022 International Conference on Trends in Quantum Computing and Emerging Business Technologies (TQCEBT),
Pune, India, Oct. 2022, pp. 1–5, doi: 10.1109/TQCEBT54229.2022.10041564.
12. J. Akonda, S. T. Alvi, C. A. A. Era, S. J. Mitu, and M. N. Uddin, “MRI Based Brain Tumor Detection Comprising a Hybrid Segmentation Technique,” 2024 Int. Conf. on Decision Aid Sciences and Applications (DASA), pp. 1–6, doi:10.1109/DASA63652.2024.10836563.
13. S. Parvathavarthini, D. V. S, K. N. S, and S. R, “Integrating YOLOV8 and Grad-CAM++ for Enhanced Brain Tumor Detection and Interpretation,” Proc. Int. Conf. on Inventive Computation Technologies (ICICT-2025), pp. 530–535, doi:10.1109/ICICT64420.2025.11004921.
14. M. V. M. Thota and B. R. Prasad, “INCS: A Novel Brain Tumor Detection Methodology Design Based on Deep Learning Assisted Intelligent Neural Classification Strategy,” 2024 Int. Conf. on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSESES), pp. 1–6, doi:10.1109/ICSES63760.2024.10910369.
15. N. Al-Ani and O. Al-Shamma, “Implementing a Novel Low Complexity CNN Model for Brain Tumor Detection,” 2022 8th Int. Conf. on Contemporary Information Technology and Mathematics (ICCITM), pp. 358–359, doi:10.1109/ICCITM56309.2022.10031630.
16. S. Desai and M. Mushrif, “Early Detection of Brain Tumor using ResNet50 and Transfer Learning,” 2024 3rd Int. Conf. on Automation, Computing and Renewable Systems (ICACRS), pp. 1488–1493, doi:10.1109/ICACRS62842.2024.10841701.
17. S. P. N, B. S, K. K. N, and P. A. Vijaya, “Detection of Human Brain Tumors Using an UWB Patch Antenna at 28GHz,” 2023 Int. Conf. on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), pp. 1–8, doi:10.1109/IITCEE57236.2023.10090949.
18. J. K. Periasamy, B. S, and J. P, “Comparison of VGG-19 and RESNET-50 Algorithms in Brain Tumor Detection,” 2023 IEEE 8th Int. Conf. for Convergence in Technology (I2CT), pp. 1–6, doi:10.1109/I2CT57861.2023.10126451.
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