A self-adaptive exhaustive search optimization-based method for restoration of bridge defects images
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Summary
A self-adaptive two-tier method for detection of noises and restoration of bridge defects images is introduced using Elman neural network coupled with invasive weed optimization algorithm to identify the type of noise that corrupts images.
- Type
- article
- Published
- 2020-01-28
- Cited by
- 16
- References
- 80
- Access
- Open access
- OpenAlex
- https://openalex.org/W3004166603
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:214198343
Keywords
Computer science, Bridge (graph theory), Noise (video), Artificial intelligence, Sensitivity (control systems)
References
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- Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
- Selection of Optimal Denoising Filter Using Quality Assessment for Potentially Lethal Optical Wound Images
- A Decision Based Unsymmetrical Trimmed Modified Winsorized Mean Filter for the Removal of High Density Salt and Pepper Noise in Images and Videos
- Application of Factor Analysis and SVM Technique in Expressway Condition Pattern Recognition
- A new image-based method for concrete bridge bottom crack detection
- Forecasting wind speed using empirical mode decomposition and Elman neural network
- A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network
- An efficient image-based damage detection for cable surface in cable-stayed bridges
- Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces
- A Study on Development of Optimal Noise Filter Algorithm for Laser Vision System in GMA Welding
- EEG signal classification using PCA, ICA, LDA and support vector machines
- Invasive weed optimization algorithm for optimization no-idle flow shop scheduling problem
- Use of Multiobjective Particle Swarm Optimization in Water Resources Management
- Reconstructing images corrupted by noise based on D–S evidence theory
- Fuzzy clustering with non-local information for image segmentation
- A comparative study of BPNN, RBFNN and ELMAN neural network for short-term electric load forecasting: A case study of Delhi region
- A genetic algorithm approach to a neural-network-based inverse kinematics solution of robotic manipulators based on error minimization
Cited by
- Integrated Condition-Based Rating Model for Sustainable Bridge Management
- A Novel Lazy Serpent Algorithm for the Prioritization of Leak Repairs in Water Networks
- Hybrid Elman Neural Network and an Invasive Weed Optimization Method for Bridge Defect Recognition
- On the hybridization of pre-trained deep learning and differential evolution algorithms for semantic crack detection and recognition in ensemble of infrastructures
- Rainfall forecasting in arid regions using an ensemble of artificial neural networks
- Improved Adaptive Neuro-Fuzzy Inference System Based on Particle Swarm Optimization Algorithm for Predicting Labor Productivity
- Optimization of English Machine Translation by Deep Neural Network under Artificial Intelligence
- Physical interpretation of machine learning-based recognition of defects for the risk management of existing bridge heritage
- Rotating Target Detection Method of Concrete Bridge Crack Based on YOLO v5
- Accurate Detection Method of Corrosion State of Steel Structure Bridge in Internet of Things Environment Based on Visual Image Characteristics
- Detecting, monitoring and modeling damage within the decision-making process in the context of managing bridges: a review
- Automated Image-Based Condition Assessment of Built Environment: A State-of-the-Art Investigation of Damage Characteristics and Detection Requirements
- Multiple Camera-Based Digital Twin Creation and Dynamic Earthquake Simulation of Historical Masonry Minarets
- Metaheuristic Algorithms Since 2020: Development, Taxonomy, Analysis, and Applications
- Computational Intelligence and Automation for Resilient Bridge Infrastructure
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