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copdapp

A medical app

copddetectionusingacoustics

Deep learning based respiratory sound analysis for detection of chronic obstructive pulmonary disease

copd_classification

copd_machine-learning

Paper:"Development of a machine learning tool in the prediction of chronic obstructive pulmonary disease in Chinese population"

copd_pred

predicting model & visualization for COPD prediction based on dataset for mortalities

cotmix

[TAI 2023] Contrastive Domain Adaptation for Time-Series via Temporal Mixup

coupled-generator-decomposition

Coupled generator decomposition for fusion of multimodal or multigroup data

cst_tva_drtl

ctcnet

脑启发 混合语音分离技术

ctgcn

CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9240056

cvan

Cross-View Alignment Network via Scale-Aware Attention for Sleep Stage Classification

deep-multitask-learning-for-fer-and-fes-based-on-selective-feature-sharing

A multi-task learning strategy for facial expression recognition and synthesis

deep-residual-shrinkage-networks

The deep residual shrinkage network is a variant of deep residual networks.

dfformer

Towards Domain Free Transformer for Generalized EEG Pre-training

distilling-step-by-step

dl4eeg-classification

The implementation of deep learning models for EEG classification.

documentation

Documentation for OpenBCI!

dosed

Dreem One Shot Detector

dsanet

Code for the CIKM 2019 paper "DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting".

dual-teacher

Official code for the NeurIPS 2023 paper "Switching Temporary Teachers for Semi-Supervised Semantic Segmentation"

ecg-classification

Code for training and test machine learning classifiers on MIT-BIH Arrhyhtmia database

ecg-classification-

ECG Arrhythmia classification using CNN

ecg-with-deep-learning

使用深度学习对人体心电数据进行多分类

ecgmatch

半监督

edpnet

Neural network for MI-EEG decoding

eeg-classification

paper for “Multiscale space-time-frequency feature-guided multitask learning CNN for motor imagery EEG classification”

eeg-deformer

时间分类任务A Convolutional Transformer to decode mental states from Electroencephalography (EEG) for Brain-Computer Interfaces (BCI)

eeg-motor-imagery-classification-cnns-tensorflow

EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow

eeg-python

Utilities and examples of EEG analysis with Python

eegdenoisenet

EEGdenoiseNet, a benchmark dataset, that is suited for training and testing deep learning-based EEG denoising models, as well as for comparing the performance across different models.