Al-juboori, A.M.; Alsaeedi, A.H.; Nuiaa, R.R.; Alyasseri, Z.A.A.; Sani, N.S.; Hadi, S.M.; Mohammed, H.J.; Musawi, B.A.; Amin, M.M.
A Hybrid Cracked Tiers Detection System Based on Adaptive Correlation Features Selection and Deep Belief Neural Networks. Symmetry 2023, 15, 358.
https://doi.org/10.3390/sym15020358
AMA Style
Al-juboori AM, Alsaeedi AH, Nuiaa RR, Alyasseri ZAA, Sani NS, Hadi SM, Mohammed HJ, Musawi BA, Amin MM.
A Hybrid Cracked Tiers Detection System Based on Adaptive Correlation Features Selection and Deep Belief Neural Networks. Symmetry. 2023; 15(2):358.
https://doi.org/10.3390/sym15020358
Chicago/Turabian Style
Al-juboori, Ali Mohsin, Ali Hakem Alsaeedi, Riyadh Rahef Nuiaa, Zaid Abdi Alkareem Alyasseri, Nor Samsiah Sani, Suha Mohammed Hadi, Husam Jasim Mohammed, Bashaer Abbuod Musawi, and Maifuza Mohd Amin.
2023. "A Hybrid Cracked Tiers Detection System Based on Adaptive Correlation Features Selection and Deep Belief Neural Networks" Symmetry 15, no. 2: 358.
https://doi.org/10.3390/sym15020358
APA Style
Al-juboori, A. M., Alsaeedi, A. H., Nuiaa, R. R., Alyasseri, Z. A. A., Sani, N. S., Hadi, S. M., Mohammed, H. J., Musawi, B. A., & Amin, M. M.
(2023). A Hybrid Cracked Tiers Detection System Based on Adaptive Correlation Features Selection and Deep Belief Neural Networks. Symmetry, 15(2), 358.
https://doi.org/10.3390/sym15020358
