tortoise-wxy's Stars
MikeCreken/Interview-site-Lan
高频大厂面试题+电子书+此仓库作为面试的一条龙服务,其中包含面试真题,简历模板,后端技术精髓,当然也有生活相关比如租房坑等,简直暖心的仓库
vkazei/fastFWI
Simple frequency domain full-waveform inversion (FWI) regularized by Sobolev space norm
TristanvanLeeuwen/SimpleFWI
Simple Matlab code for testing optimization algorithms on seismic inverse problems.
izzatum/FWIGAN
FWIGAN: Full-Waveform Inversion with Deep Adversarial Learning
cxdsz/stock-price-prediction-algorithms
使用随机森林、bp神经网络、LSTM神经网络、GRU对股票收盘价进行回归预测。Random forest, BP neural network, LSTM neural network and GRU are used to predict the closing price.
vvanggeng/TSC-CNN
基于一维卷积神经网络(1D-CNN)的多元时间序列分类
HiddenSharp/LSTM-SVM-RF-time-series
Regression prediction of time series data using LSTM, SVM and random forest. 使用LSTM、SVM、随机森林对时间序列数据进行回归预测,注释拉满。
goodboyv/Sklearn_Mochine_leanring
利用sklearn实现机器学习算法:线性回归、逻辑回归、决策树、随机森林、SVM等
m516825/Conditional-GAN
Anime Generation
BraveY/AI-with-code
AI学习过程中的实操代码
rasmusbergpalm/DeepLearnToolbox
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
cmjagtap/Stock_Price_Predication
I have implemented Recurrent Neural Network (RNN model) to predict the future stock prices and compare it with linear regression.
CakeBnut1996/GAN-Time-Series-Regression
This script is used for numerical values prediction. The example is next two-hour traffic speed prediction based on historical speeds.
zhangqianhui/AdversarialNetsPapers
Awesome paper list with code about generative adversarial nets
dhavalc25/Image-Denoising
Noise Reduction in Images using Wavelet Shrinkage with Soft Thresholding
nayeem78/Wavelet-Transform-for-Image-Processing
Wavelet Transform for Image decomposition, Image reconstruction and Image denoising
himynameisfuego/wavelet-denoising
Speech enhancement based on adaptive wavelet denoising on multitaper spectrum
GKalliatakis/Wavelet-decomposition-and-Filter-bank
The wavelet transform and its applications in image denoising
LabForComputationalVision/matlabPyrTools
MatLab tools for multi-scale image processing, including Laplacian pyramids, Wavelets, and Steerable Pyramids
wargod797/Fault_diagnosis_ballbearing_wavelet
Bearing fault diagnosis is important in condition monitoring of any rotating machine. Early fault detection in machinery can save millions of dollars in emergency maintenance cost. Different techniques are used for fault analysis such as short time Fourier transforms (STFT), Wavelet analysis (WA), cepstrum analysis, Model based analysis, etc. we have doing detecting bearing faults using FFT and by using Wavelet analysis more specifically wavelet Analysis up to two levels of approximations and detail components. The analysis is carried out offline in MATLAB. Diagnosing the faults before in hand can save the millions of dollars of industry and can save the time as well. It has been found that Condition monitoring of rolling element bearings has enabled cost saving of over 50% as compared with the old traditional methods. The most common method of monitoring the condition of rolling element bearing is by using vibration signal analysis. Measure the vibrations of machine recorded by velocity
smousavi05/Denoising-BTwavelet
This repository contains MATLAB scripts and sample seismic data for appying seismid denoising proposed in: "Hybrid Seismic Denoising Using Higher‐Order Statistics and Improved Wavelet Block Thresholding"
lpj0/MWCNN
Multi-level Wavelet-CNN for Image Restoration
eunh/low_dose_CT
Deep Convolutional Framelet Denoising for Low-Dose CT via Wavelet Residual Network
Ayatans/Machine-Learning-homework
Matlab Coding homework for Machine Learning
zhanwen/MathModel
研究生数学建模,本科生数学建模、数学建模竞赛优秀论文,数学建模算法,LaTeX论文模板,算法思维导图,参考书籍,Matlab软件教程,PPT
AIBigTruth/CNN_faces_recognition
基于卷积神经网络(CNN)的人脸在线识别系统
Mikoto10032/DeepLearning
深度学习入门教程, 优秀文章, Deep Learning Tutorial
apachecn/ailearning
AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
leena201818/radioml
深度学习在软件无线电领域的应用
Qinbf/tf-model-zoo
tensorflow实现的深度学习应用和模型