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Research Article

Brain Tumour Detection Using Deep Learning and Angular

Somaanath M U1 Hariharapranav R S2 Kowsik J3 Lavanya C4
1234 Computer Science & Engineering, Bannari Amman Institute of Technology, Tamil Nadu, India.

Published Online: March-April 2023

Pages: 19-22

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References

1. Ali, T. M., Nawaz, A., Rehman, A. U., Ahmad, R. Z., Javed, A. R., Gadekallu, T. R., et al. (2022). Asequential machine learningcum-attention mechanism for effective segmentation of brain tumor.
2. Amin, J., Sharif, M., Raza, M., Saba, T., Sial, R., and Shad, S. A. (2020).Brain tumor detection: a long short-term memory (lstm)-based
learning model.
3. Dahiwade, D., Patle, G., and Meshram, E. (2019). Designing disease prediction model using machine learning approach.
4. Kumar, D. M., Satyanarayana, D., and Prasad, M. (2021). Mri brain tumor detection using optimal possibilistic fuzzy c-means
clustering algorithm and adaptive k-nearest neighbor classifier. J. Ambient. Intell. Humaniz Comput. 12, 2867–2880. doi:
10.1007/s12652-020-02444-7
5. Senan, E. M., Jadhav, M. E., Rassem, T. H., Aljaloud, A. S., Mohammed, B. A., and Al-Mekhlafi, Z. G.(2022). Early diagnosis of brain
tumour mri images using hybrid techniques between deep and machine learning Survey.
6. Tiwari, P., Pant, B., Elarabawy, M. M., Abd-Elnaby, M., Mohd, N., Dhiman, G., et al. (2022). Cnn based multiclass brain tumor
detection using medical imaging. Comput. Intell. Neurosci. 2022, 1830010. doi: 10.1155/2022/1830010.
7. lya Sutskever, Oriol Vinyals, Quoc V. Le. Sequence to Sequence Learning with Neural Networks. DEC 2014

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