AIMC Topic: Neural Networks, Computer

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Development of predictive algorithms for the wear resistance of denture teeth materials.

Journal of the mechanical behavior of biomedical materials
OBJECTIVES: To investigate the wear resistance of conventional, CAD-milled and 3D-printed denture teeth in vitro with simulated aging. To use the collected data to train single time series sample model LSTM and provide proof of concept.

CNN Hardware Accelerator for Real-Time Bearing Fault Diagnosis.

Sensors (Basel, Switzerland)
This paper introduces a one-dimensional convolutional neural network (CNN) hardware accelerator. It is crafted to conduct real-time assessments of bearing conditions using economical hardware components, implemented on a field-programmable gate array...

Quantification of Structural Defects Using Pixel Level Spatial Information from Photogrammetry.

Sensors (Basel, Switzerland)
Aging infrastructure has drawn increased attention globally, as its collapse would be destructive economically and socially. Precise quantification of minor defects is essential for identifying issues before structural failure occurs. Most studies me...

ConvCoroNet: a deep convolutional neural network optimized with iterative thresholding algorithm for Covid-19 detection using chest X-ray images.

Journal of biomolecular structure & dynamics
Covid-19 is a global pandemic. Early and accurate detection of positive cases prevent the further spread of this epidemic and help to treat rapidly the infected patients. During the peak of this epidemic, there was an insufficiency of Covid-19 test k...

Increasing-Margin Adversarial (IMA) training to improve adversarial robustness of neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Deep neural networks (DNNs) are vulnerable to adversarial noises. Adversarial training is a general and effective strategy to improve DNN robustness (i.e., accuracy on noisy data) against adversarial noises. However, DNN mod...

Simulator, machine learning, and artificial intelligence: Time has come to assist prenatal ultrasound diagnosis.

Journal of clinical ultrasound : JCU
In this Commentary authors investigated and extended the role of simulator in assisting obstetric sonographers in training program. The interconnection of different digitalized technologies such as digital data, artificial neuronal and convolutional ...

Accurate prediction of isothermal gas chromatographic Kováts retention indices.

Journal of chromatography. A
We describe a freely available web server called Retention Index Predictor (RIpred) (https://ripred.ca) that rapidly and accurately predicts Gas Chromatographic Kováts Retention Indices (RI) using SMILES strings as chemical structure input. RIpred pe...

Shall we always use hydraulic models? A graph neural network metamodel for water system calibration and uncertainty assessment.

Water research
Representing reality in a numerical model is complex. Conventionally, hydraulic models of water distribution networks are a tool for replicating water supply system behaviour through simulation by means of approximation of physical equations. A calib...

Node-Loss Detection Methods for CZ Silicon Single Crystal Based on Multimodal Data Fusion.

Sensors (Basel, Switzerland)
Monocrystalline silicon is an important raw material in the semiconductor and photovoltaic industries. In the Czochralski (CZ) method of growing monocrystalline silicon, various factors may cause node loss and lead to the failure of crystal growth. C...

A Light-Weight Artificial Neural Network for Recognition of Activities of Daily Living.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) is essential for the development of robots to assist humans in daily activities. HAR is required to be accurate, fast and suitable for low-cost wearable devices to ensure portable and safe assistance. Current computat...