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Found 14 papers, 3 papers with code
Graph Neural Networks in EEG-based Emotion Recognition: A Survey
Besides, there is neither a comprehensive review nor guidance for constructing GNNs in EEG-based emotion recognition.
Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation
In terms of the AMG mode, Hi-SAM segments text stroke foreground masks initially, then samples foreground points for hierarchical text mask generation and achieves layout analysis in passing.
Ranked #1 on
Hierarchical Text Segmentation
on HierText
Bidirectional Trained Tree-Structured Decoder for Handwritten Mathematical Expression Recognition
The Handwritten Mathematical Expression Recognition (HMER) task is a critical branch in the field of OCR.
scBeacon: single-cell biomarker extraction via identifying paired cell clusters across biological conditions with contrastive siamese networks
Despite the breakthroughs in biomarker discovery facilitated by differential gene analysis, challenges remain, particularly at the single-cell level.
Multi-stream Cell Segmentation with Low-level Cues for Multi-modality Images
Afterward, we train a separate segmentation model for each category using the images in the corresponding category.
EENED: End-to-End Neural Epilepsy Detection based on Convolutional Transformer
Recently Transformer and Convolution neural network (CNN) based models have shown promising results in EEG signal processing.
EEG-based Sleep Staging with Hybrid Attention
Specifically, we propose a well-designed spatio-temporal attention mechanism to adaptively assign weights to inter-channels and intra-channel EEG segments based on the spatio-temporal relationship of the brain during different sleep stages.
An EEG Channel Selection Framework for Driver Drowsiness Detection via Interpretability Guidance
However, the raw EEG data is inherently noisy and redundant, which is neglected by existing works that just use single-channel EEG data or full-head channel EEG data for model training, resulting in limited performance of driver drowsiness detection.
Interpretable and Robust AI in EEG Systems: A Survey
In this paper, we present the first comprehensive survey and summarize the interpretable and robust AI techniques for EEG systems.
Vision-Language Adaptive Mutual Decoder for OOV-STR
However, in real-world scenarios, out-of-vocabulary (OOV) words are of great importance and SOTA recognition models usually perform poorly on OOV settings.
Video Forgery Detection Using Multiple Cues on Fusion of EfficientNet and Swin Transformer
The first is that capturing the general clue of artifacts is difficult.
Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning
We assume that this context is not accessible to a learner agent who can only observe the expert data.
Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint
Considering that multi-modal MR images can reflect different tumor biological properties, we develop a novel multi-modal tumor segmentation network (MMTSN) to robustly segment brain tumors based on multi-modal MR images.
Multi-Modality Pathology Segmentation Framework: Application to Cardiac Magnetic Resonance Images
The PRSN is designed to segment pathological region based on the result of ASSN, in which a fusion block based on channel attention is proposed to better aggregate multi-modality information from multi-modality CMR images.
