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Acknowledgements

            The authors would like to thank Universiti Kebangsaan Malaysia for providing financial support under the
        “Geran Universiti Penyelidikan” research grant, GUP-2020-064.


        References

        Arahusky.(2021).Tensorflow-Segmentation. Retrieved from https://github.com/arahusky/ Tensorflow-
        Segmentation.
        Bulla, P., Anantha, L., & Peram, S. (2020). Deep Neural Networks with Transfer Learning Model for Brain
        Tumors Classification. Traitement du Signal, 37(4).
        Beckett, A. J., Dadakova, T., Townsend, J., Huber, L., Park, S., & Feinberg, D. A. (2020). Comparison of
        BOLD and CBV using 3D EPI and 3D GRASE for cortical layer functional MRI at 7 T. Magnetic resonance
        in medicine, 84(6), 3128-3145.
        Damodharan, S., & Raghavan, D. (2015). Combining tissue segmentation and neural network for brain tumor
        detection. International Arab Journal of Information Technology (IAJIT), 12(1).
        Deepak,  S.,  &  Ameer,  P.  (2020).  MSG-GAN  Based  Synthesis  of  Brain  MRI  with  Meningioma  for  Data
        Augmentation.IEEE International Conference on Electronics, Computing and Communication Technologies
        (CONECCT).
        Divya, S., Suresh, L. P., & John, A. (2020). A Deep Transfer Learning framework for Multi Class Brain Tumor
        Classification using MRI. 2nd International Conference on Advances in Computing, Communication Control
        and Networking (ICACCCN).
        Ide, M., Atsumi, T., Chakrabarty, M., Yaguchi, A., Umesawa, Y., Fukatsu, R., & Wada, M. (2020). Neural
        basis of extremely high temporal sensitivity: insights from a patient with autism. Frontiers in Neuroscience, 14,
        340.
        Mahayuddin, Z. R., & Saif, A. S. (2020). A Comprehensive Review Towards Segmentation And Detection Of
        Cancer Cell And Tumor For Dynamic 3d Reconstruction. Asia-Pacific Journal of Information Technology and
        Multimedia, 9(1), 28-39.
        Müller, S., Weickert, J., & Graf, N. (2016). Automatic brain tumor segmentation with a fast Mumford-Shah
        algorithm. Medical Imaging 2016: Image Processing.
        Pizer, S. M. (1990). Contrast-limited adaptive histogram equalization: Speed and effectiveness stephen m. pizer,
        r. eugene johnston, james p. ericksen, bonnie c. yankaskas, keith e. muller medical image display research
        group. First Conference on Visualization in Biomedical Computing, Atlanta, Georgia.
        Rathi, V. G. P., & Palani, S. (2015). Brain tumor detection and classification using deep learning classifier on
        MRI images. Research Journal of Applied Sciences, Engineering and Technology, 10(2), 177-187.
        Saif,  A.  S.,  &  Mahayuddin,  Z.  R.  (2020).  Vehicle  Detection  for  Collision  Avoidance  Using  Vision  based
        Approach: A Constructive Review. Solid State Technology, 63(2s), 2861-2869.
        Saif, A. F. M. S., & Prabuwono, A. S. (2015). Moment Feature Based Fast Feature Extraction Algorithm for
        Moving Object Detection Using Aerial Images. PLoS One, 10(6).
        Saif, A. F. M. S., Mahayuddin, Z. R., & Prabuwono, A. S. (2015). Efficiency Measurement of Various Denoise
        Techniques  for  Moving  Object  Detection  Using  Aerial  Images.  International  Conference  on  Electrical
        Engineering and Informatics (ICEEI).
        Saif, A. F. M. S., Prabuwono, A. S., & Mahayuddin, Z. R. (2014). Moving object detection using dynamic
        motion modeling from UAV aerial images. Scientific World Journal, 2014.
        Schawkat, K., Ciritsis, A., von Ulmenstein, S., Honcharova-Biletska, H., Jüngst, C., Weber, A., . . . Reiner, C.
        S. (2020). Diagnostic accuracy of texture analysis and machine learning for quantification of liver fibrosis in
        MRI: correlation with MR elastography and histopathology. European radiology, 30(8), 4675-4685.







        E- Proceedings of The 5th International Multi-Conference on Artificial Intelligence Technology (MCAIT 2021)   [94]
        Artificial Intelligence in the 4th Industrial Revolution
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