AIMC Topic: Cues

Clear Filters Showing 11 to 20 of 98 articles

Machine learning based classification of excessive smartphone users via neuronal cue reactivity.

Psychiatry research. Neuroimaging
Excessive Smartphone Use (ESU) poses a significant challenge in contemporary society, yet its recognition as a distinct disorder remains ambiguous. This study aims to address this gap by leveraging functional magnetic resonance imaging (fMRI) data an...

EEG based depression detection by machine learning: Does inner or overt speech condition provide better biomarkers when using emotion words as experimental cues?

Journal of psychiatric research
BACKGROUND: Objective diagnostic approaches need to be tested to enhance the efficacy of depression detection. Non-invasive EEG-based identification represents a promising area.

Holistic-Guided Disentangled Learning With Cross-Video Semantics Mining for Concurrent First-Person and Third-Person Activity Recognition.

IEEE transactions on neural networks and learning systems
The popularity of wearable devices has increased the demands for the research on first-person activity recognition. However, most of the current first-person activity datasets are built based on the assumption that only the human-object interaction (...

Risk and prosocial behavioural cues elicit human-like response patterns from AI chatbots.

Scientific reports
Emotions, long deemed a distinctly human characteristic, guide a repertoire of behaviors, e.g., promoting risk-aversion under negative emotional states or generosity under positive ones. The question of whether Artificial Intelligence (AI) can posses...

A Generative Model to Embed Human Expressivity into Robot Motions.

Sensors (Basel, Switzerland)
This paper presents a model for generating expressive robot motions based on human expressive movements. The proposed data-driven approach combines variational autoencoders and a generative adversarial network framework to extract the essential featu...

Use of a humanoid robot for auditory psychophysical testing.

PloS one
Tasks in psychophysical tests can at times be repetitive and cause individuals to lose engagement during the test. To facilitate engagement, we propose the use of a humanoid NAO robot, named Sam, as an alternative interface for conducting psychophysi...

Improving the acceptability of social robots: Make them look different from humans.

PloS one
The social robots market will grow considerably in the coming years. What the arrival of these new kind of social agents means for society, however, is largely unknown. Existing cases of robot abuse point to risks of introducing such artificial socia...

Negation and speculation processing: A study on cue-scope labelling and assertion classification in Spanish clinical text.

Artificial intelligence in medicine
Natural Language Processing (NLP) based on new deep learning technology is contributing to the emergence of powerful solutions that help healthcare providers and researchers discover valuable patterns within insurmountable volumes of health records a...

Cultural differences in joint attention and engagement in mutual gaze with a robot face.

Scientific reports
Joint attention is a pivotal mechanism underlying human ability to interact with one another. The fundamental nature of joint attention in the context of social cognition has led researchers to develop tasks that address this mechanism and operationa...

Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection From Point Clouds.

IEEE transactions on pattern analysis and machine intelligence
Previous works for LiDAR-based 3D object detection mainly focus on the single-frame paradigm. In this paper, we propose to detect 3D objects by exploiting temporal information in multiple frames, i.e., point cloud videos. We empirically categorize th...