ljxstc's Stars
yangluo7/CAME
The official implementation of "CAME: Confidence-guided Adaptive Memory Optimization"
Juntongkuki/Hyper-Compression
fyancy/ProMo
A Bayesian Probabilistic Framework for Mechanical Fault Diagnosis
YMLZS/Transformer_BearingFaultDiagnosis
Using transformer to realize Bearing Fault Diagnosis
Gnomeek/PolyU_report_Latex_template_library
lucidrains/tab-transformer-pytorch
Implementation of TabTransformer, attention network for tabular data, in Pytorch
pkumivision/FFC
This is an official pytorch implementation of Fast Fourier Convolution.
FangBo-0219/MNAD
Minimum Noise Amplitude Deconvolution
fonderxu/Bearing-fault-diagnosis-datasets
This repository currently provides common and public avaiable bearing vibration datasets, including downloading, preprocessing and loading.
jianzhang96/MSD
mobile phone screen surface defect segmentation (detection) dataset.
AliMorty/Markov-Random-Field-Project
This project has two parts. In part one, we use markov random field to denoise an image. In Part two, we use similar model for image segmentation.
asdvfghg/QCNN_for_bearing_diagnosis
Andy-zhujunwen/UNET-ZOO
including unet,unet++,attention-unet,r2unet,cenet,segnet ,fcn.
MIC-DKFZ/nnUNet
MrGiovanni/UNetPlusPlus
[IEEE TMI] Official Implementation for UNet++
milesial/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
lhyfst/knowledge-distillation-papers
knowledge distillation papers
linmh0130/CyclicSpectrumPlot
Provide MATLAB functions to plot Cyclic Spectrum.
Nicolasnull/using-a-cnn-to-classify-cyclostationary-data
efsierraa/PyCycloVarREB
Cyclostationary analysis in angular domain for bearing fault identification
SSTGroup/Cyclostationary-Signal-Processing
aresmiki/A-case-of-the-intelligent-bearing-fault-diagnosis
This is a case of bearing fault intelligent diagnosis. The program is written in MATLAB. The main techniques used are feature detection and neural network. This code comes from the undergraduate course assignment. The code has been written for 8 years. Because many students need such a simple case study, so it was sent out
Jintao-Huang/torch_tf2_study
努力学习深度学习(已废弃), 见仓库ml_alg
qianlima-lab/ADSN
The paper "Adversarial Dynamic Shapelet Network"
patrick-kidger/generalised_shapelets
Code for "Generalised Interpretable Shapelets for Irregular Time Series"
benibaeumle/Learning-Shapelets
A PyTorch implementation of learning shapelets from the paper Grabocka et al., „Learning Time-Series Shapelets“.
lukemelas/deep-spectral-segmentation
[CVPR 2022] Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization
locuslab/deq
[NeurIPS'19] Deep Equilibrium Models
liguge/Fault-diagnosis-for-small-samples-based-on-attention-mechanism
基于注意力机制的少量样本故障诊断 pytorch
xmu-xiaoma666/External-Attention-pytorch
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐