Irfan Ahmed Usmani^1,*, Muhammad Tahir Qadri¹, Razia Zia¹, Asif Aziz², Farheen Saeed³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4369-4392, 2022, DOI:10.32604/cmc.2022.030698

Abstract Knowledge-based transfer learning techniques have shown good performance for brain tumor classification, especially with small datasets. However, to obtain an optimized model for targeted brain tumor classification, it is challenging to select a pre-trained deep learning (DL) model, optimal values of hyperparameters, and optimization algorithm (solver). This paper first presents a brief review of recent literature related to brain tumor classification. Secondly, a robust framework for implementing the transfer learning technique is proposed. In the proposed framework, a Cartesian product matrix is generated to determine the optimal values of the two important hyperparameters: batch size and learning rate. An extensive… More >

S. Satham Hussain¹, G. Muhiuddin^2,*, N. Durga³, D. Al-Kadi⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 559-580, 2022, DOI:10.32604/cmes.2022.017032

Abstract The partition of indeterminacy function of the neutrosophic set into the contradiction part and the ignorance part represent the quadripartitioned single valued neutrosophic set. In this work, the new concept of quadripartitioned bipolar single valued neutrosophic graph is established, and the operations on it are studied. The Cartesian product, cross product, lexicographic product, strong product and composition of quadripartitioned bipolar single valued neutrosophic graph are investigated. The proposed concepts are illustrated with examples. More >