abby722 Goto Github PK

abby722

Config files for my GitHub profile.

addto15

Imagine you are playing Tic Tac Toe with an AI robot and this project stimulates such kind of process with some flaws to be improved.

ai4animation

Bringing Characters to Life with Computer Brains in Unity

bm3d.torch

torch wrappers for bm3d denoising

dataset_ballpacking

dncnn

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)

ess

European Spallation Source facility bespoke, neutron scattering tools based on scipp.

fucking-algorithm

刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

furry-fiesta

git_learning

github-pages-with-jekyll

github-slideshow

A robot powered training repository :robot:

gre-model-analytical-writing

some samples of analytical writing

hdn

This repository hosts the code for HDN (associated with the paper https://arxiv.org/pdf/2104.01374.pdf) for pixel and structured noise removal for microscopy and natural image datasets

kair

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

lidia-denoiser

LIDIA: Lightweight Learned Image Denoising with Instance Adaptation (NTIRE, 2020)

lodoind

Code for paper "LoDoInd: Introducing A Benchmark Low-dose Industrial CT Dataset and Enhancing Denoising with 2.5D Deep Learning Techniques."

machine-learning-notes

class 1

mandelbrot_gpu

Compute the Mandlebrot set on CPU vs GPU using TensorFlow

merge-conflicts

n2v

This is the implementation of Noise2Void training.

notes-from-python-class

pyclesperanto_prototype

GPU-accelerated bio-image analysis focusing on 3D+t microscopy image data

pydom

Sharpness Estimation for Document and Scene Images

red-cnn

Pytorch Implementation of Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)

reviewing-a-pull-request

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.