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image-denoising-state-of-the-art

imagedenoisinggan

Image Denoising with Generative Adversarial Network

imagedenoisingksvd

MATLAB implementation of the paper "Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries"

imagefeaturedetector

A C++ Qt GUI desktop program to calculate Harris, FAST, SIFT and SURF image features with OpenCV

imageprocessing

利用VS2017平台实现图像处理的一些基本算法。图形平滑、图像锐化、图像增强、傅里叶变换、行程编码

intracluster-slrma

hyper-spectral image denoising

javafamily

【互联网一线大厂面试+学习指南】进阶知识完全扫盲：涵盖高并发、分布式、高可用、微服务等领域知识，作者风格幽默，看起来津津有味，把学习当做一种乐趣，何乐而不为，后端同学必看，前端同学我保证你也看得懂，看不懂你加我微信骂我渣男就好了。

jcsprout

👨‍🎓 Java Core Sprout : basic, concurrent, algorithm

kbr-tc-and-rpca

code of KBR_TC and KBR_RPCA

kdrsdl

Code for Robust Kronecker-Decomposable Component Analysis (ICCV 2017)

keras-yolo3

A Keras implementation of YOLOv3 (Tensorflow backend)

l0learn

Efficient Algorithms for L0 Regularized Learning

learn-python3

Learn Python 3 Sample Code

learning-opencv-3_examples

lrslibrary

Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos

machine-learning-from-scratch

常用机器学习的算法简洁实现

machine-learning-with-python

内容摘自'**大学MOOC'

machinelearning

Basic Machine Learning and Deep Learning

ml-examples

some machine learning examples

ml-in-action-code-and-note

:chart_with_upwards_trend:Machine Learning code in Python3.x. Some notes about the practices please click here:（personal notes, for reference only）

mmdetection

Open MMLab Detection Toolbox and Benchmark

mr-amp

Multi-resolution approximate message passing algorithm for multi-resolution compressed sensing problem

msrcr-restoration

Retinex Algorithms: C++ source code of SSR, MSR, MSRCR algorithm

multi-layer-rpca

Method Multi-Layer Robust Principal Component Analysis. This method was introduced in the paper Camera-Trap Images Segmentation using Multi-Layer Robust Principal Component Analysis

myrepository

n3net

Neural Nearest Neighbors Networks (NIPS*2018)

ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

nnls-sdp

NLS version 0: A MATLAB software for semidefinite programming

noise-adaptive-switching-non-local-means

Aiming at the removal of salt-and-pepper noise, a noise adaptive switching non-local means denoising algorithm (NASNLM) is proposed in this program. For noise detection, the pixels of image are divided into the noise and the non-noise points. For filtering, four different filtering techniques are adopted: switching filtering, noise adaptive median filtering, edge-perserving filtering and non-local means filtering. Switching filtering can keep the gray-value of non-noise points unchanged. Noise adaptive median filtering can suppress the high-density salt-and-pepper noise. Edge-preserving filtering can preserve more image edges and details. Non-local means filtering can further improve the ability of noise suppression and detail maintenance. Experiments demonstrate that for removal of the high-density salt-and-pepper noise by NASNLM algorithm, a better denoising effect is obtained than other methods.

o2o-coupon-usage-forecast

1st Place Solution for O2O Coupon Usage Forecast