AIMC Topic: Neural Networks, Computer

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Research on a Bearing Fault Enhancement Diagnosis Method with Convolutional Neural Network Based on Adaptive Stochastic Resonance.

Sensors (Basel, Switzerland)
As a powerful feature extraction tool, a convolutional neural network (CNN) has strong adaptability for big data applications such as bearing fault diagnosis, whereas the classification performance is limited when the quality of raw signals is poor. ...

Performance Comparison of Multiple Convolutional Neural Networks for Concrete Defects Classification.

Sensors (Basel, Switzerland)
Periodical vision-based inspection is a principal form of structural health monitoring (SHM) technique. Over the last decades, vision-based artificial intelligence (AI) has successfully facilitated an effortless inspection system owing to its excepti...

Microsatellite Uncertainty Control Using Deterministic Artificial Intelligence.

Sensors (Basel, Switzerland)
This manuscript explores the applications of deterministic artificial intelligence (DAI) in a space environment in response to unknown sensor noise and sudden changes in craft physical parameters. The current state of the art literature has proposed ...

A New Hybrid Neural Network Deep Learning Method for Protein-Ligand Binding Affinity Prediction and De Novo Drug Design.

International journal of molecular sciences
Accurately predicting ligand binding affinity in a virtual screening campaign is still challenging. Here, we developed hybrid neural network (HNN) machine deep learning methods, HNN-denovo and HNN-affinity, by combining the 3D-CNN (convolutional neur...

A novel genetic-artificial neural network based age estimation system.

Scientific reports
Age estimation is the ability to predict the age of an individual based on facial clues. This could be put to practical use in underage voting detection, underage driving detection, and overage sportsmen detection. To date, no popular automatic age e...

Novel deep learning hybrid models (CNN-GRU and DLDL-RF) for the susceptibility classification of dust sources in the Middle East: a global source.

Scientific reports
Dust storms have many negative consequences, and affect all kinds of ecosystems, as well as climate and weather conditions. Therefore, classification of dust storm sources into different susceptibility categories can help us mitigate its negative eff...

A parallel integrated learning technique of improved particle swarm optimization and BP neural network and its application.

Scientific reports
Swarm intelligence algorithm has attracted a lot of interest since its development, which has been proven to be effective in many application areas. In this study, an enhanced integrated learning technique of improved particle swarm optimization and ...

Electronic thygmonasty model inbiomimetic robot.

Bioinspiration & biomimetics
Direct contact of random objects from the open environment to the panel surface of an electronic device may reduce the work efficiency and cause permanent damage. However, there is a possible way to solve this problem, notably by implementing an adap...

Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey.

Physics in medicine and biology
Reinforcement learning takes sequential decision-making approaches by learning the policy through trial and error based on interaction with the environment. Combining deep learning and reinforcement learning can empower the agent to learn the interac...

DeepCAN: A Modular Deep Learning System for Automated Cell Counting and Viability Analysis.

IEEE journal of biomedical and health informatics
Precise and quick monitoring of key cytometric features such as cell count, size, morphology, and DNA content is crucial in life science applications. Traditionally, image cytometry relies on visual inspection of hemocytometers. This approach is erro...