MrShing's Stars
DenisDsh/PyTorch-Deep-CORAL
This is a PyTorch implementation of the Unsupervised Domain Adaptation method proposed in the paper Deep CORAL: Correlation Alignment for Deep Domain Adaptation. Baochen Sun and Kate Saenko (ECCV 2016).
pmorerio/minimal-entropy-correlation-alignment
Code for the paper "Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation", ICLR 2018
erlendd/ddan
Deep domain adaptation networks (DDAN) library for Python with TensorFlow.
SNBQT/Limited-Data-Rolling-Bearing-Fault-Diagnosis-with-Few-shot-Learning
This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning
shuo-zhou/pydale
Domain Adaptation Learning in Python
mingzhangPHD/Transfer-Learning-for-Fault-Diagnosis
This repository is for the transfer learning or domain adaptive with fault diagnosis.
MorvanZhou/tutorials
机器学习相关教程
PeterJackNaylor/InternWork2
my ipython notebooks
minjiang/iglda
jindongwang/transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
shiluqiang/RBF_NN_Python
Python code of RBF neural network classification model
srk-srinivasan/Permutation-Entropy
Python and R Codes for Computing Permutation Entropy
raady07/CNN-for-bearing-fault-diagnosis
CNN applied to bearing signals for analysis
TimePickerWang/MachineLearning
Machine Learning in Action学习笔记,一个文件夹代表一个算法,每个文件夹包含算法所需的数据集、源码和图片,图片放在pic文件夹中,数据集放在在Data文件夹内。书中的代码是python2的,有不少错误,这里代码是我用python3写的,且都能直接运行
cokelaer/spectrum
Spectral Analysis in Python
drrelyea/spgl1
Port of SPGL1 to python
jiemojiemo/TensorFlow-SimpleRNN
shanpoqq/DiagnosisDL2TF
使用TensorFlow建立简单的轴承故障诊断模型
zhengyima/mnist-classification
Pytorch、Scikit-learn实现多种分类方法,包括逻辑回归(Logistic Regression)、多层感知机(MLP)、支持向量机(SVM)、K近邻(KNN)、CNN、RNN,极简代码适合新手小白入门,附英文实验报告(ACM模板)
guanyibing/Fault-diagnosis
基于深度学习机械设备故障诊断模型
f-koehler/compsens
One-dimensional signal analysis using compressed sensing
Prakash2403/Compressed-Sensing
A simple implementation of compressed sensing in python
okaminu/guoliu-gedimai
Rolling bearings defect detection using vibration and signal analysis methods. Application used for Master Thesis