AIMC Topic: Humans

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Using a multi-strain infectious disease model with physical information neural networks to study the time dependence of SARS-CoV-2 variants of concern.

PLoS computational biology
With the ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its increasing adaptation to humans, several variants of concern (VOCs) and variants of interest (VOIs) have been identified since late 2020. These include...

Neuroevolution insights into biological neural computation.

Science (New York, N.Y.)
This article reviews existing work and future opportunities in neuroevolution, an area of machine learning in which evolutionary optimization methods such as genetic algorithms are used to construct neural networks to achieve desired behavior. The ar...

VSR-Net: Vessel-Like Structure Rehabilitation Network With Graph Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The morphologies of vessel-like structures, such as blood vessels and nerve fibres, play significant roles in disease diagnosis, e.g., Parkinson's disease. Although deep network-based refinement segmentation and topology-preserving segmentation metho...

Rethinking Copy-Paste for Consistency Learning in Medical Image Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Semi-supervised learning based on consistency learning offers significant promise for enhancing medical image segmentation. Current approaches use copy-paste as an effective data perturbation technique to facilitate weak-to-strong consistency learnin...

A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm.

PloS one
In the field of robotic arm trajectory imitation learning, Gaussian Mixture Models are widely used for their ability to capture the characteristics of complex trajectories. However, one major challenge in utilizing these models lies in the initializa...

Fast fault diagnosis of smart grid equipment based on deep neural network model based on knowledge graph.

PloS one
The smart grid is on the basis of physical grid, introducing all kinds of advanced communications technology and form a new type of power grid. It can not only meet the demand of users and realize the optimal allocation of resources, but also improve...

SignFormer-GCN: Continuous sign language translation using spatio-temporal graph convolutional networks.

PloS one
Sign language is a complex visual language system that uses hand gestures, facial expressions, and body movements to convey meaning. It is the primary means of communication for millions of deaf and hard-of-hearing individuals worldwide. Tracking phy...

Hybrid-RViT: Hybridizing ResNet-50 and Vision Transformer for Enhanced Alzheimer's disease detection.

PloS one
Alzheimer's disease (AD) is a leading cause of disability worldwide. Early detection is critical for preventing progression and formulating effective treatment plans. This study aims to develop a novel deep learning (DL) model, Hybrid-RViT, to enhanc...

4D trajectory prediction and conflict detection in terminal areas based on an improved convolutional network.

PloS one
At present, the passenger traffic volume of civil aviation is gradually increasing, and the scale of the airline network is gradually expanding. In order to optimize the air traffic service mode more safely and scientifically, the International Civil...

A Tutorial on the Use of Artificial Intelligence Tools for Facial Emotion Recognition in R.

Multivariate behavioral research
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection ...