[HTML][HTML] Evaluation and optimisation of pre-trained CNN models for asphalt pavement crack detection and classification

S Matarneh, F Elghaish, FP Rahimian… - Automation in …, 2024 - Elsevier
This study explored the performance of ten pre-trained CNN architectures in detecting and
classifying asphalt pavement cracks from images. A comparison of eight optimisation …

AO-HRCNN: archimedes optimization and hybrid region-based convolutional neural network for detection and classification of diabetic retinopathy

S Krishnamoorthy, yu Weifeng, J Luo… - Artificial Intelligence …, 2023 - Springer
Diabetic Retinopathy (DR) primarily affects a set of lesions in the eyes, causing retinal
degeneration and loss of vision. The DR features serve as a crucial component for …

A new framework for collaborative filtering with p-moment-based similarity measure: Algorithm, optimization and application

FE Alsaadi, Z Wang, NS Alharbi, Y Liu… - Knowledge-based …, 2022 - Elsevier
In this paper, a general framework of user-based collaborative filtering (CF) is developed
with a new p-moment-based similarity measure. The p-moment-based statistics (PMS) of …

ERMN: An enhanced meta-learning approach for state of health estimation of lithium-ion batteries

G Ma, X Yang, S Xu, C Cheng, X He - Journal of Energy Storage, 2023 - Elsevier
To ensure the safety of lithium-ion batteries (LIBs), accurately estimating the state of health
(SOH) of LIBs is crucial for end-users. Challenged by new working conditions and limited …

Multidirectional Information Fusion for Complex Defect Reconstruction Based on Induced Current Thermo-Electrical Impedance Tomography

X Zhang, L Bai, L Tian, J Ai, Y Liang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The recently proposed induced current thermo-electrical impedance tomography (ICTEIT) is
a nondestructive evaluation method for nonferromagnetic metal materials. The method …