zhengjing8628's repositories
Accelerating-CNN-with-FPGA
This project accelerates CNN computation with the help of FPGA, for more than 50x speed-up compared with CPU.
ADCME.jl
Automatic Differentiation Library for Computational and Mathematical Engineering
AdFem.jl
Innovative, efficient, and computational-graph-based finite element simulator for inverse modeling
ADSeismic.jl
A General Approach to Seismic Inversion Problems using Automatic Differentiation
baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
CDnCNN-B-tensorflow
CDnCNN-B for blind color image denoising - Tensorflow implementation
CERP_Pytorch
CNN-Event detector and RNN-Phase picker, implemented with Pytorch
ConvDAE
convolutional denoising autoencoder
deeplogs
Velocity model building by deep learning. Multi-CMP gathers are mapped into velocity logs.
DIDN
Pytorch Implementation of "Deep Iterative Down-Up CNN for Image Denoising".
DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)
dvdnet
DVDnet: A Simple and Fast Network for Deep Video Denoising
Earthquake-Prediction
To predict the time that an earthquake will occur in a laboratory test using Scikit-Learn (Pedregosa et al. (2011), XGBoost (Chen & Guestrin, 2016) and LightGBM (Ke, et al., 2017) libraries for machine learning and support. The laboratory test applies shear forces to a sample of earth and rock containing a fault line. If the physics are ultimately shown to scale from the laboratory to the field, researchers will have the potential to improve earthquake hazard assessments that could save lives and billions of dollars in infrastructure. The metric used is Mean Absolute Error (MAE) and thus a lower value is better with zero representing a perfect fit.
ECNDNet
imag-denosing, CNN
FFDNet
FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising (TIP, 2018)
FwiFlow.jl
Elastic Full Waveform Inversion for subsurface flow problems with intrusive automatic differentiation
HSI-SDeCNN
Source code of "A Single Model CNN for Hyperspectral Image Denoising"
KAIR
Image Restoration Toolbox (PyTorch). Training and testing codes for DnCNN, FFDNet, SRMD, DPSR, MSRResNet, ESRGAN, IMDN
reproducible-image-denoising-state-of-the-art
Collection of popular and reproducible image denoising works.
SincNet
SincNet is a neural architecture for efficiently processing raw audio samples.
Speech-enhancement
Deep learning for audio denoising
STEAD
STanford EArthquake Dataset (STEAD):A Global Data Set of Seismic Signals for AI
vnlnet
VNLnet is a Video denoising CNN with Non-locality information
wavetorch
🌊 Numerically solving and backpropagating through the wave equation