Mehwash Farooqui1, Atta Rahman2,*, Latifa Alsuliman1, Zainab Alsaif1, Fatimah Albaik1, Cadi Alshammari1, Razan Sharaf1, Sunday Olatunji1, Sara Waslallah Althubaiti1, Hina Gull3
CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2587-2605, 2024, DOI:10.32604/cmc.2024.055262
- 18 November 2024
Abstract The proposed study focuses on the critical issue of corrosion, which leads to significant economic losses and safety risks worldwide. A key area of emphasis is the accuracy of corrosion detection methods. While recent studies have made progress, a common challenge is the low accuracy of existing detection models. These models often struggle to reliably identify corrosion tendencies, which are crucial for minimizing industrial risks and optimizing resource use. The proposed study introduces an innovative approach that significantly improves the accuracy of corrosion detection using a convolutional neural network (CNN), as well as two pretrained… More >
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