nicolepingz Goto Github PK

auto-eeg-diagnosis-comparison

focal-loss-pytorch

全中文注释.(The loss function of retinanet based on pytorch).(You can use it on one-stage detection task or classifical task, to solve data imbalance influence).用于one-stage目标检测算法,提升检测效果.你也可以在分类任务中使用该损失函数,解决数据不平衡问题.

hsuantienlin-ml-camp

machine-learning-approaches-for-biomarker-identification

A Machine learning approach for the identification of biomarkers in osteoarthritis, although methodology is generic enough to applied for other biomedical data. Dataset is provided by CHECK (Cohort Hip & Cohort Knee) In total 8 Machine Learning models are attached using feature selectors RFE and Relief, with classifiers Random Forest (RF), Logistic Regression (LR), Support Vector Classifier (SVC) and Xgboost (Xgb)

ntu-hsuantienlin-machinelearning

signal2image-modules-in-deep-neural-networks-for-eeg-classification

Code used for 'Signal2Image Modules in Deep Neural Networks for EEG Classification' presented at EMBC 2019.

tfdecomp

Matlab package for time-frequency analysis of EEG data through wavelet decomposition

toemr

中医骨科电子病历数据集

vae

a simple vae and cvae from keras

withwangyiping