AIMC Topic: Humans

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LidSonic V2.0: A LiDAR and Deep-Learning-Based Green Assistive Edge Device to Enhance Mobility for the Visually Impaired.

Sensors (Basel, Switzerland)
Over a billion people around the world are disabled, among whom 253 million are visually impaired or blind, and this number is greatly increasing due to ageing, chronic diseases, and poor environments and health. Despite many proposals, the current d...

A Parallel Classification Model for Marine Mammal Sounds Based on Multi-Dimensional Feature Extraction and Data Augmentation.

Sensors (Basel, Switzerland)
Due to the poor visibility of the deep-sea environment, acoustic signals are often collected and analyzed to explore the behavior of marine species. With the progress of underwater signal-acquisition technology, the amount of acoustic data obtained f...

A Review on Human Comfort Factors, Measurements, and Improvements in Human-Robot Collaboration.

Sensors (Basel, Switzerland)
As the development of robotics technologies for collaborative robots (COBOTs), the applications of human-robot collaboration (HRC) have been growing in the past decade. Despite the tremendous efforts from both academia and industry, the overall usage...

A Hybrid Model Based on Improved Transformer and Graph Convolutional Network for COVID-19 Forecasting.

International journal of environmental research and public health
The coronavirus disease 2019 (COVID-19) has spread rapidly around the world since 2020, with a significant fatality rate. Until recently, numerous countries were unable to adequately control the pandemic. As a result, COVID-19 trend prediction has be...

Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study.

BMC bioinformatics
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have resulted in significant enthusiasm for their promise in healthcare. Despite this, prospective randomized controlled trials and successful clinical implementation remain limited. ...

Research on imaging method of driver's attention area based on deep neural network.

Scientific reports
In the driving process, the driver's visual attention area is of great significance to the research of intelligent driving decision-making behavior and the dynamic research of driving behavior. Traditional driver intention recognition has problems su...

Comparing two machine learning approaches in predicting lupus hospitalization using longitudinal data.

Scientific reports
Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease characterized by flares ranging from mild to life-threatening. Severe flares and complications can require hospitalizations, which account for most of the direct costs of SLE ca...

Perception without preconception: comparison between the human and machine learner in recognition of tissues from histological sections.

Scientific reports
Deep neural networks (DNNs) have shown success in image classification, with high accuracy in recognition of everyday objects. Performance of DNNs has traditionally been measured assuming human accuracy is perfect. In specific problem domains, howeve...

Development of a deep learning network for Alzheimer's disease classification with evaluation of imaging modality and longitudinal data.

Physics in medicine and biology
. Neuroimaging uncovers important information about disease in the brain. Yet in Alzheimer's disease (AD), there remains a clear clinical need for reliable tools to extract diagnoses from neuroimages. Significant work has been done to develop deep le...