AIMC Topic: Emotions

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Label-less Learning for Emotion Cognition.

IEEE transactions on neural networks and learning systems
In this paper, we propose a label-less learning for emotion cognition (LLEC) to achieve the utilization of a large amount of unlabeled data. We first inspect the unlabeled data from two perspectives, i.e., the feature layer and the decision layer. By...

Constructing a Personalized Cross-Day EEG-Based Emotion-Classification Model Using Transfer Learning.

IEEE journal of biomedical and health informatics
State-of-the-art electroencephalogram (EEG)-based emotion-classification works indicate that a personalized model may not be well exploited until sufficient labeled data are available, given a substantial EEG non-stationarity over days. However, it i...

Depression recognition using machine learning methods with different feature generation strategies.

Artificial intelligence in medicine
The diagnosis of depression almost exclusively depends on doctor-patient communication and scale analysis, which have the obvious disadvantages such as patient denial, poor sensitivity, subjective biases and inaccuracy. An objective, automated method...

Embodiment into a robot increases its acceptability.

Scientific reports
Recent studies have shown how embodiment induced by multisensory bodily interactions between individuals can positively change social attitudes (closeness, empathy, racial biases). Here we use a simple neuroscience-inspired procedure to beam our huma...

Learning-based classification of valence emotion from electroencephalography.

The International journal of neuroscience
The neuroimaging research field has been revolutionized with the development of human cognitive functions without the use of brain pathways. To assist such systems, electroencephalography (EEG) based measures play an important role. In this study, th...

A multimodal convolutional neuro-fuzzy network for emotion understanding of movie clips.

Neural networks : the official journal of the International Neural Network Society
Multimodal emotion understanding enables AI systems to interpret human emotions. With accelerated video surge, emotion understanding remains challenging due to inherent data ambiguity and diversity of video content. Although deep learning has made a ...

Incorporating Conversational Strategies in a Social Robot to Interact with People with Dementia.

Dementia and geriatric cognitive disorders
BACKGROUND: Socially assistive robots (SARs) have the potential to assist nonpharmacological interventions based on verbal communication to support the care of persons with dementia (PwDs). However, establishing verbal communication with a PwD is cha...

Adaptive Learning Emotion Identification Method of Short Texts for Online Medical Knowledge Sharing Community.

Computational intelligence and neuroscience
The medical knowledge sharing community provides users with an open platform for accessing medical resources and sharing medical knowledge, treatment experience, and emotions. Compared with the recipients of general commodities, the recipients in the...

Pairwise Interactions among Brain Regions Organize Large-Scale Functional Connectivity during Execution of Various Tasks.

Neuroscience
Spatially separated brain areas interact with each other to form networks with coordinated activities, supporting various brain functions. Interaction structures among brain areas have been widely investigated through pairwise measures. However, inte...

Quantifying ultrasonic mouse vocalizations using acoustic analysis in a supervised statistical machine learning framework.

Scientific reports
Examination of rodent vocalizations in experimental conditions can yield valuable insights into how disease manifests and progresses over time. It can also be used as an index of social interest, motivation, emotional development or motor function de...