[HTML][HTML] Application of meta-heuristic algorithms for training neural networks and deep learning architectures: A comprehensive review
M Kaveh, MS Mesgari - Neural Processing Letters, 2023 - Springer
The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …
and deep learning (DL) architectures is considered one of the most challenging machine …
Vision-based concrete crack detection using a hybrid framework considering noise effect
Diagnosing surface cracks of concrete structures has been a critical aspect of assessing
structural integrity. Existing diagnosis technologies are time-consuming, subjective, and …
structural integrity. Existing diagnosis technologies are time-consuming, subjective, and …
Torsional capacity evaluation of RC beams using an improved bird swarm algorithm optimised 2D convolutional neural network
This study presents the application of deep learning technology in torsional capacity
evaluation of reinforced concrete (RC) beams. A data-driven model based on 2D …
evaluation of reinforced concrete (RC) beams. A data-driven model based on 2D …
Research overview on edge detection algorithms based on deep learning and image fusion
B Tian, W Wei - Security and Communication Networks, 2022 - Wiley Online Library
Edge detection is a boundary‐based segmentation method to extract important information
from an image, and it is a research hotspot in the fields of computer vision and image …
from an image, and it is a research hotspot in the fields of computer vision and image …
Corrosion and coating defect assessment of coal handling and preparation plants (CHPP) using an ensemble of deep convolutional neural networks and decision …
In view of the problems of ineffective feature extraction and low detection accuracy in
existing detection system, this study presents a novel machine vision-based approach …
existing detection system, this study presents a novel machine vision-based approach …
[HTML][HTML] Integration of TLS-derived Bridge Information Modeling (BrIM) with a Decision Support System (DSS) for digital twinning and asset management of bridge …
In the current modern era of information and technology, the concept of Building Information
Modeling (BIM), has made revolutionary changes in different aspects of engineering design …
Modeling (BIM), has made revolutionary changes in different aspects of engineering design …
Deep learning-based obstacle-avoiding autonomous UAVs with fiducial marker-based localization for structural health monitoring
This paper proposes a framework for obstacle-avoiding autonomous unmanned aerial
vehicle (UAV) systems with a new obstacle avoidance method (OAM) and localization …
vehicle (UAV) systems with a new obstacle avoidance method (OAM) and localization …
Deep learning of electromechanical impedance for concrete structural damage identification using 1-D convolutional neural networks
D Ai, F Mo, J Cheng, L Du - Construction and Building Materials, 2023 - Elsevier
Common damages in concrete materials and structures are usually in small sizes at initial
stage, which induce small stiffness and mass loss being difficult to evaluate severity level …
stage, which induce small stiffness and mass loss being difficult to evaluate severity level …
[HTML][HTML] Hybrid SFNet model for bone fracture detection and classification using ML/DL
An expert performs bone fracture diagnosis using an X-ray image manually, which is a time-
consuming process. The development of machine learning (ML), as well as deep learning …
consuming process. The development of machine learning (ML), as well as deep learning …
Automated identification of compressive stress and damage in concrete specimen using convolutional neural network learned electromechanical admittance
D Ai, F Mo, Y Han, J Wen - Engineering Structures, 2022 - Elsevier
For the first time, this paper proposed a simple two-dimensional convolutional neural
network (2-D CNN) integrated with electromechanical admittance (EMA, inverse of …
network (2-D CNN) integrated with electromechanical admittance (EMA, inverse of …