AIMC Topic: Humans

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Synthesising 2D Video from 3D Motion Data for Machine Learning Applications.

Sensors (Basel, Switzerland)
To increase the utility of legacy, gold-standard, three-dimensional (3D) motion capture datasets for computer vision-based machine learning applications, this study proposed and validated a method to synthesise two-dimensional (2D) video image frames...

Cross-Modal Reconstruction for Tactile Signal in Human-Robot Interaction.

Sensors (Basel, Switzerland)
A human can infer the magnitude of interaction force solely based on visual information because of prior knowledge in human-robot interaction (HRI). A method of reconstructing tactile information through cross-modal signal processing is proposed in t...

Automated Detection of Myocardial Infarction and Heart Conduction Disorders Based on Feature Selection and a Deep Learning Model.

Sensors (Basel, Switzerland)
An electrocardiogram (ECG) is an essential piece of medical equipment that helps diagnose various heart-related conditions in patients. An automated diagnostic tool is required to detect significant episodes in long-term ECG records. It is a very cha...

PassTCN-PPLL: A Password Guessing Model Based on Probability Label Learning and Temporal Convolutional Neural Network.

Sensors (Basel, Switzerland)
The frequent incidents of password leakage have increased people's attention and research on password security. Password guessing is an essential part of password cracking and password security research. The progression of deep learning technology pr...

Multi-Level Classification of Driver Drowsiness by Simultaneous Analysis of ECG and Respiration Signals Using Deep Neural Networks.

International journal of environmental research and public health
The high number of fatal crashes caused by driver drowsiness highlights the need for developing reliable drowsiness detection methods. An ideal driver drowsiness detection system should estimate multiple levels of drowsiness accurately without interv...

Semi-supervised classifier guided by discriminator.

Scientific reports
Some machine learning applications do not allow for data augmentation or are applied to modalities where the augmentation is difficult to define. Our study aimed to develop a new method in semi-supervised learning (SSL) applicable to various modaliti...

Empirical Analysis of Early Childhood Enlightenment Education Using Neural Network.

Computational intelligence and neuroscience
This exploration aims to study the value orientation and essence of early childhood enlightenment education based on the deep neural network (DNN). Based on the acquisition and feature learning of cross-media education big data, the DNN correlation l...

The Use of Thinking Visualization Techniques in College Teaching Based on Improved Genetic Algorithms.

Computational intelligence and neuroscience
Current educational resources do not maximize energy efficiency, and scientific and proven teaching methods are necessary for today's university education to help achieve the integration of teaching resources and improve teaching quality. This study ...

Research on the Analysis of Correlation Factors of English Translation Ability Improvement Based on Deep Neural Network.

Computational intelligence and neuroscience
This paper adopts the algorithm of the deep neural network to conduct in-depth research and analysis on the factors associated with the improvement of English translation ability. This study focuses on text complexity, adding discourse complexity fea...

Biomedical Diagnosis of Leukemia Using a Deep Learner Classifier.

Computational intelligence and neuroscience
Leukemia cancer is the most common type of cancer that occurs in childhood. The most common types are acute lymphocytic leukemia (ALL) and acute myelogenous leukemia (AML) which affect children and adults, respectively. Several health issues occur du...