- Published
- 2021-06-11
- Venue
- IRBM, vol. 43, no. 4, pp. 290-299
- Cited by
- 498
- Open access
- No free copy found
- DOI
- 10.1016/j.irbm.2021.06.003
Cite this paper
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- APA 7
Khairandish, M. O., Sharma, M., Jain, V. K., Chatterjee, J. M., & Jhanjhi, N. Z. (2021). A Hybrid CNN-SVM Threshold Segmentation Approach for Tumor Detection and Classification of MRI Brain Images. IRBM, 43(4), 290–299. https://doi.org/10.1016/j.irbm.2021.06.003
- MLA 9
Khairandish, Mohammad Omid, et al. "A Hybrid CNN-SVM Threshold Segmentation Approach for Tumor Detection and Classification of MRI Brain Images." IRBM, vol. 43, no. 4, 2021, pp. 290–299, https://doi.org/10.1016/j.irbm.2021.06.003.
- Chicago
Khairandish, Mohammad Omid, Meenakshi Sharma, Vishal Kumar Jain, Jyotir Moy Chatterjee, and Noor Zaman Jhanjhi. "A Hybrid CNN-SVM Threshold Segmentation Approach for Tumor Detection and Classification of MRI Brain Images." IRBM 43, no. 4 (2021): 290–299. https://doi.org/10.1016/j.irbm.2021.06.003.
- GOST
Khairandish M. O., Sharma M., Jain V. K. [и др.] A Hybrid CNN-SVM Threshold Segmentation Approach for Tumor Detection and Classification of MRI Brain Images // IRBM. — 2021. — Vol. 43, № 4. — P. 290–299. — URL: https://doi.org/10.1016/j.irbm.2021.06.003
- BibTeX
@article{khairandish2021hybrid, title = {{A Hybrid CNN-SVM Threshold Segmentation Approach for Tumor Detection and Classification of MRI Brain Images}}, author = {Mohammad Omid Khairandish and Meenakshi Sharma and Vishal Kumar Jain and Jyotir Moy Chatterjee and Noor Zaman Jhanjhi}, journal = {IRBM}, year = {2021}, volume = {43}, number = {4}, pages = {290--299}, doi = {10.1016/j.irbm.2021.06.003}, url = {https://doi.org/10.1016/j.irbm.2021.06.003} }- RIS
TY - JOUR AU - Khairandish, Mohammad Omid AU - Sharma, Meenakshi AU - Jain, Vishal Kumar AU - Chatterjee, Jyotir Moy AU - Jhanjhi, Noor Zaman TI - A Hybrid CNN-SVM Threshold Segmentation Approach for Tumor Detection and Classification of MRI Brain Images JO - IRBM VL - 43 IS - 4 SP - 290 EP - 299 PY - 2021 DA - 2021/06/11 DO - 10.1016/j.irbm.2021.06.003 UR - https://doi.org/10.1016/j.irbm.2021.06.003 ER -