weiming1122 / 1D-ResNet-SE-LSTM
Codes for the paper 'Automatic sleep staging by a hybrid model based on deep 1D-ResNet-SE and LSTM with single-channel raw EEG signals' https://www.biorxiv.org/content/10.1101/2023.03.29.534672v1 & https://peerj.com/articles/cs-1561/
☆22Updated last year
Alternatives and similar repositories for 1D-ResNet-SE-LSTM:
Users that are interested in 1D-ResNet-SE-LSTM are comparing it to the libraries listed below
- This model replaces the original CompactCNN with a Transformer model. It is designed to classify 1D EEG signals for the purpose of dr…☆12Updated last year
- Code for paper "MSA-CNN: A Lightweight Multi-Scale CNN with Attention for Sleep Stage Classification"☆11Updated last month
- A Residual based Attention Model for EEG basedSleep Staging☆11Updated 3 years ago
- This paper was submitted to ICASSP 2023: Exploiting Interactivity and Heterogeneity for Sleep Stage Classification via Heterogeneous Grap…☆25Updated last year
- Codes for our paper "Triple-Attention-based Spatio-Temporal-Spectral Convolutional Network for Epileptic Seizure Prediction "☆21Updated 2 years ago
- ☆13Updated last year
- The Cross-modal SleepTransformer is a deep learning model designed for sleep stage classification based on multimodal physiological signa…☆17Updated 7 months ago
- Emotion classification from Brain EEG signals using a hybrid CNN-Transformer model and various ML algorithms.☆22Updated last year
- ☆18Updated 4 months ago
- In this Basic Tutorial, I have used 1DCNN for EEG classification using random dataset, You can use your own dataset☆19Updated 5 years ago
- SleepPrintNet: A Multivariate Multimodal Neural Network based on Physiological Time-series for Automatic Sleep Staging☆34Updated 11 months ago
- Construct a model, which contains channel-attention, CNN, LSTM, self-attention, to classify EEG data;☆11Updated 3 years ago
- [IEEE JBHI] "MultiChannelSleepNet: A Transformer-Based Model for Automatic Sleep Stage Classification With PSG"☆49Updated last year
- Transfer learning for multi source EEG-emotion-classification☆14Updated 4 years ago
- Emotion-Classification-by-EEG-DEAP-Dataset implemented in 2DCNNN-LSTM-1DCNN+GRU and the 1D_cnn+gru model gives the highest accuracy☆10Updated last year
- MMCNN: A Multi-branch Multi-scale Convolutional Neural Network for Motor Imagery Classification☆22Updated 3 years ago
- A Pytorch implementation of our paper "Adaptive Spatial-Temporal Aware Graph Learning for EEG-based Emotion Recognition".☆16Updated last year
- ☆53Updated 3 years ago
- The model for the paper “Spatio-Temporal-Spectral Hierarchical Graph Convolutional Network With Semisupervised Active Learning for Patien…☆17Updated 3 years ago
- Emotion recognition base on EEG.☆16Updated last year
- Emotional Classification with the DEAP dataset using EEGLAB, matlab and python. Currently in the status of developing a more efficient an…☆22Updated 4 years ago
- Different methods(STFT, CWT) transform EEG signal into image visualization☆13Updated 4 years ago
- Official implementation of our MICCAI 2022 paper "mulEEG: A Multi-View Representation Learning on EEG Signals"☆34Updated 2 years ago
- 基于小波变换和卷积神经网络的脑电运动成像信号分类☆44Updated 4 years ago
- [IEEE J-BHI-2024] The PyTorch implementation of MASA-TCN☆37Updated 4 months ago
- ☆19Updated 2 years ago
- An EEG-based emotion recognition system using Simple Recurrent Units(SRU) in Pytorch library. It identifies three emotions: positive, neu…☆11Updated 3 years ago
- SalientSleepNet: Multimodal Salient Wave Detection Network for Sleep Staging☆53Updated 3 years ago
- The final project for ECE C147/C247, which evaluates the performance of CNN + Transformer and CNN + GRU + SimpleRNN models on an EEG data…☆12Updated 2 years ago
- EEG emotion recognition based on Temporal convolutional network☆24Updated 6 years ago