AIMC Topic: Learning

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Curricula for teaching end-users to kinesthetically program collaborative robots.

PloS one
Non-expert users can now program robots using various end-user robot programming methods, which have widened the use of robots and lowered barriers preventing robot use by laypeople. Kinesthetic teaching is a common form of end-user robot programming...

Learning Skill Characteristics From Manipulations.

IEEE transactions on neural networks and learning systems
Percutaneous coronary intervention (PCI) has increasingly become the main treatment for coronary artery disease. The procedure requires high experienced skills and dexterous manipulations. However, there are few techniques to model PCI skill so far. ...

DHI-GAN: Improving Dental-Based Human Identification Using Generative Adversarial Networks.

IEEE transactions on neural networks and learning systems
In this work, a novel semisupervised framework is proposed to tackle the small-sample problem of dental-based human identification (DHI), achieving enhanced performance via a "classifying while generating" paradigm. A generative adversarial network (...

Application of transfer learning to predict drug-induced human in vivo gene expression changes using rat in vitro and in vivo data.

PloS one
The liver is the primary site for the metabolism and detoxification of many compounds, including pharmaceuticals. Consequently, it is also the primary location for many adverse reactions. As the liver is not readily accessible for sampling in humans;...

A Scoping Review of the Use of Robotics Technologies for Supporting Social-Emotional Learning in Children with Autism.

Journal of autism and developmental disorders
This scoping review synthesises the current research into robotics technologies for promoting social-emotional learning in children with autism spectrum disorder. It examines the types of robotics technologies employed, their applications, and the ga...

Diagnosing injection-production system faults in the same well using the rough set-LVQ neural network.

PloS one
This study proposed a reverse calculation model of the unique rod pump injection and production system structures in the same well to diagnose and resolve defects, after which dynamometer diagrams of the system production and injection pumps were dra...

VGAE-MCTS: A New Molecular Generative Model Combining the Variational Graph Auto-Encoder and Monte Carlo Tree Search.

Journal of chemical information and modeling
Molecular generation is crucial for advancing drug discovery, materials science, and chemical exploration. It expedites the search for new drug candidates, facilitates tailored material creation, and enhances our understanding of molecular diversity....

Students' Foreign Language Learning Adaptability and Mental Health Supported by Artificial Intelligence.

Journal of autism and developmental disorders
The rapid development of social reform and the economy has brought great challenges to the mental health of college students. However, there are few studies on the impact of these psychological problems on college students' English learning. As a spe...

N-of-one differential gene expression without control samples using a deep generative model.

Genome biology
Differential analysis of bulk RNA-seq data often suffers from lack of good controls. Here, we present a generative model that replaces controls, trained solely on healthy tissues. The unsupervised model learns a low-dimensional representation and can...

Spatio-Temporal Explanation of 3D-EEGNet for Motor Imagery EEG Classification Using Permutation and Saliency.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Recently, convolutional neural network (CNN)-based classification models have shown good performance for motor imagery (MI) brain-computer interfaces (BCI) using electroencephalogram (EEG) in end-to-end learning. Although a few explainable artificial...