AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Steel

Showing 1 to 10 of 20 articles

Clear Filters

Research on Mechanical and Carbonization Properties of Hybrid Fiber Iron Tailings Concrete Based on Deep Learning.

Computational intelligence and neuroscience
Iron tailings sand is a kind of mineral waste, and open-air storage is a common treatment method for iron tailings, which not only has a huge impact on the ecological environment but also occupies a lot of land resources. Therefore, the preparation o...

Corroded Bolt Identification Using Mask Region-Based Deep Learning Trained on Synthesized Data.

Sensors (Basel, Switzerland)
The performance of a neural network depends on the availability of datasets, and most deep learning techniques lack accuracy and generalization when they are trained using limited datasets. Using synthesized training data is one of the effective ways...

A pixel-wise framework based on convolutional neural network for surface defect detection.

Mathematical biosciences and engineering : MBE
The automatic surface defect detection system supports the real-time surface defect detection by reducing the information and high-lighting the critical defect regions for high level image under-standing. However, the defects exhibit low contrast, di...

Loosening Identification of Multi-Bolt Connections Based on Wavelet Transform and ResNet-50 Convolutional Neural Network.

Sensors (Basel, Switzerland)
A high-strength bolt connection is the key component of large-scale steel structures. Bolt loosening and preload loss during operation can reduce the load-carrying capacity, safety, and durability of the structures. In order to detect loosening damag...

Integrated Damage Location Diagnosis of Frame Structure Based on Convolutional Neural Network with Inception Module.

Sensors (Basel, Switzerland)
Accurate damage location diagnosis of frame structures is of great significance to the judgment of damage degree and subsequent maintenance of frame structures. However, the similarity characteristics of vibration data at different damage locations a...

A Novel CNN-LSTM Hybrid Model for Prediction of Electro-Mechanical Impedance Signal Based Bond Strength Monitoring.

Sensors (Basel, Switzerland)
The recent application of deep learning for structural health monitoring systems for damage detection has potential for improvised structure performance and maintenance for long term durability, and reliable strength. Advancements in electro-mechanic...

Frame Structure Fault Diagnosis Based on a High-Precision Convolution Neural Network.

Sensors (Basel, Switzerland)
Structural health monitoring and fault diagnosis are important scientific issues in mechanical engineering, civil engineering, and other disciplines. The basic premise of structural health work is to be able to accurately diagnose the fault in the st...

Hazard source detection of longitudinal tearing of conveyor belt based on deep learning.

PloS one
Belt tearing is the main safety accident of belt conveyor. The main cause of tearing is the doped bolt and steel in the conveying belt. In this paper, the bolt and steel are identified as the Hazard source of tear. In this paper, bolt and steel are d...

The Prediction of Steel Bar Corrosion Based on BP Neural Networks or Multivariable Gray Models.

Computational intelligence and neuroscience
The corrosion of steel bars in concrete has a significant impact on the durability of constructed structures. Based on the gray relational analysis (GRA) of the accelerated corrosion data and practical engineering data using MATLAB, a back propagatio...

Performance evaluation of machine learning techniques in surface morphology and corrosion prediction for A286 3D printed micro-lattice structures.

PloS one
The development of lightweight, corrosion-resistant metallic lattice structures has gained significant attention in aerospace, defense, and structural applications, where material durability and weight optimization are critical. This study investigat...