AIMC Topic: Neural Networks, Computer

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Fault Recognition Method Based on Attention Mechanism and the 3D-UNet.

Computational intelligence and neuroscience
Oil and gas reservoirs are of great significance for economic benefits. Faults act as important conduits for transporting hydrocarbons and as essential sealing conditions. The location and morphology of faults reflect changes in the shape of the stra...

Construction of Home Product Design System Based on Self-Encoder Depth Neural Network.

Computational intelligence and neuroscience
The traditional home product design system mainly depends on relatively shallow learning network, relatively simple embedded technology and Internet of things technology. The traditional home design system mainly depends on the traditional self-encod...

Land Resource Use Classification Using Deep Learning in Ecological Remote Sensing Images.

Computational intelligence and neuroscience
Aiming at the problems that the traditional remote sensing image classification methods cannot effectively integrate a variety of deep learning features and poor classification performance, a land resource use classification method based on a convolu...

Efficient Framework for Detection of COVID-19 Omicron and Delta Variants Based on Two Intelligent Phases of CNN Models.

Computational and mathematical methods in medicine
INTRODUCTION: While the COVID-19 pandemic was waning in most parts of the world, a new wave of COVID-19 Omicron and Delta variants in Central Asia and the Middle East caused a devastating crisis and collapse of health-care systems. As the diagnostic ...

Detection of plane in remote sensing images using super-resolution.

PloS one
The object detection of remote sensing image often has low accuracy and high missed or false detection rate due to the large number of small objects, instance level noise and cloud occlusion. In this paper, a new object detection model based on SRGAN...

Training of artificial neural networks with the multi-population based artifical bee colony algorithm.

Network (Bristol, England)
Nowadays, artificial intelligence has gained recognition in every aspect of life. Artificial neural networks, one of the most efficient artificial intelligence techniques, is remarkably successful in computers' acquisition of the learning and interpr...

Organization of a Latent Space structure in VAE/GAN trained by navigation data.

Neural networks : the official journal of the International Neural Network Society
We present a novel artificial cognitive mapping system using generative deep neural networks, called variational autoencoder/generative adversarial network (VAE/GAN), which can map input images to latent vectors and generate temporal sequences intern...

Attributed graph clustering with multi-task embedding learning.

Neural networks : the official journal of the International Neural Network Society
Attributed graph clustering is challenging as it needs to effectively combine both graph structure and node feature information to accomplish node clustering. Recent studies mostly adopt graph neural networks to learn node embeddings, then apply trad...

Automatic Evaluation of Motor Rehabilitation Exercises Based on Deep Mixture Density Neural Networks.

Journal of biomedical informatics
An automatic assessment system for physical telerehabilitation could reduce the time and cost of treatments. But such assessment involves stochastic uncertainties, nonlinearities, and complexities of human movement. Probabilistic models and deep stru...

MS-ResNet: disease-specific survival prediction using longitudinal CT images and clinical data.

International journal of computer assisted radiology and surgery
PURPOSE: Medical imaging data of lung cancer in different stages contain a large amount of time information related to its evolution (emergence, development, or extinction). We try to explore the evolution process of lung images in time dimension to ...