Pmr: Prototypical modal rebalance for multimodal learning
Multimodal learning (MML) aims to jointly exploit the common priors of different modalities to
compensate for their inherent limitations. However, existing MML methods often optimize a …
compensate for their inherent limitations. However, existing MML methods often optimize a …
Adaptive neural decision tree for EEG based emotion recognition
Y Zheng, J Ding, F Liu, D Wang - Information Sciences, 2023 - Elsevier
An adaptive neural decision tree is investigated to recognize electroencephalogram (EEG)
emotion signal with ability of intelligently selecting network structure. Firstly, to overcome …
emotion signal with ability of intelligently selecting network structure. Firstly, to overcome …
ViTFER: facial emotion recognition with vision transformers
In several fields nowadays, automated emotion recognition has been shown to be a highly
powerful tool. Mapping different facial expressions to their respective emotional states is the …
powerful tool. Mapping different facial expressions to their respective emotional states is the …
Adaptive multimodal emotion detection architecture for social robots
J Heredia, E Lopes-Silva, Y Cardinale… - Ieee …, 2022 - ieeexplore.ieee.org
Emotion recognition is a strategy for social robots used to implement better Human-Robot
Interaction and model their social behaviour. Since human emotions can be expressed in …
Interaction and model their social behaviour. Since human emotions can be expressed in …
Video2music: Suitable music generation from videos using an affective multimodal transformer model
Numerous studies in the field of music generation have demonstrated impressive
performance, yet virtually no models are able to directly generate music to match …
performance, yet virtually no models are able to directly generate music to match …
EmoMV: Affective music-video correspondence learning datasets for classification and retrieval
HTP Thao, G Roig, D Herremans - Information Fusion, 2023 - Elsevier
Studies in affective audio–visual correspondence learning require ground-truth data to train,
validate, and test models. The number of available datasets together with benchmarks …
validate, and test models. The number of available datasets together with benchmarks …
AMSA: Adaptive multimodal learning for sentiment analysis
Efficient recognition of emotions has attracted extensive research interest, which makes new
applications in many fields possible, such as human-computer interaction, disease …
applications in many fields possible, such as human-computer interaction, disease …
Building multimodal knowledge bases with multimodal computational sequences and generative adversarial networks
D Chen, R Zhang - IEEE Transactions on Multimedia, 2023 - ieeexplore.ieee.org
Conventional knowledge graphs (KGs) are composed solely of entities, attributes, and
relationships, which poses challenges for enhancing multimodal knowledge representation …
relationships, which poses challenges for enhancing multimodal knowledge representation …
Prediction of emotional empathy in intelligent agents to facilitate precise social interaction
The research area falls under the umbrella of affective computing and seeks to introduce
intelligent agents by simulating emotions artificially and encouraging empathetic behavior in …
intelligent agents by simulating emotions artificially and encouraging empathetic behavior in …
Emotion classification from speech and text in videos using a multimodal approach
MC Caschera, P Grifoni, F Ferri - Multimodal Technologies and …, 2022 - mdpi.com
Emotion classification is a research area in which there has been very intensive literature
production concerning natural language processing, multimedia data, semantic knowledge …
production concerning natural language processing, multimedia data, semantic knowledge …