Emotion recognition using electroencephalogram (EEG) mainly has two
scen...
Insufficient data is a long-standing challenge for Brain-Computer Interf...
Protein-protein interactions (PPIs) are crucial in various biological
pr...
Domain shift and label scarcity heavily limit deep learning applications...
Domain shift has been a long-standing issue for medical image segmentati...
We used two multimodal models for continuous valence-arousal recognition...
While deep learning methods hitherto have achieved considerable success ...
Steady-state visual evoked potential (SSVEP) is one of the most commonly...
Learning time-series representations when only unlabeled data or few lab...
While there have been increased researches using deep learning technique...
While deep models have shown promising performance in medical image
segm...
With large-scale well-labeled datasets, deep learning has shown signific...
Label scarcity has been a long-standing issue for biomedical image
segme...
We propose a cross-modal co-attention model for continuous emotion
recog...
The success of deep convolutional neural networks (DCNNs) benefits from ...
Deep learning (DL) has been widely investigated in a vast majority of
ap...
The domain adaption (DA) problem on symmetric positive definite (SPD)
ma...
Sleep staging is of great importance in the diagnosis and treatment of s...
We propose an audio-visual spatial-temporal deep neural network with: (1...
Learning decent representations from unlabeled time-series data with tem...
Deep learning has achieved promising segmentation performance on 3D left...
In this paper, we propose LGG, a neurologically inspired graph neural
ne...
In this paper, we propose TSception, a multi-scale convolutional neural
...
Lack of adequate training samples and noisy high-dimensional features ar...
Dementia is one of the main causes of cognitive decline. Since the major...
Image segmentation is one of the most essential biomedical image process...
One way to achieve eXplainable artificial intelligence (XAI) is through ...
The success of deep learning (DL) methods in the Brain-Computer Interfac...
In this paper, we propose a deep learning framework, TSception, for emot...
Convolutional Neural Network (CNN) has been successfully applied on
clas...
Steady-state visual evoked potentials (SSVEP) brain-computer interface (...
When artificial intelligence is used in the medical sector, interpretabi...
Reducing the lateral scale of two-dimensional (2D) materials to
one-dime...
Recently, artificial intelligence, especially machine learning has
demon...
Synthesis of advanced inorganic materials with minimum number of trials ...