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csgm

Code to reproduce results from the paper: "Compressed Sensing using Generative Models".

d-amp_toolbox

This package contains the code to run Learned D-AMP, D-AMP, D-VAMP, D-prGAMP, and DnCNN algorithms. It also includes code to train Learned D-AMP, DnCNN, and Deep Image Prior U-net using the SURE loss.

darknet

Windows and Linux version of Darknet Yolo v3 & v2 Neural Networks for object detection (Tensor Cores are used)

darknet2ncnn

Darknet2ncnn converts the darknet model to the ncnn model

datastructs_and_algorithm

Data struct and algorithm introduction and implementation in C/C++/Java.

dbpn-pytorch

The project is an official implement of our CVPR2018 paper "Deep Back-Projection Networks for Super-Resolution" (Winner of NTIRE2018 and PIRM2018)

deep-image-prior

Image restoration with neural networks but without learning.

deep_learning_object_detection

A paper list of object detection using deep learning.

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.

deformable-detr

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

detectron2

Detectron2 is FAIR's next-generation platform for object detection and segmentation.

detnet

cvpr2018 detnet(tsinghua university)

detouring-matching-pursuit-algorithm-in-compressed-sensing

压缩感知中迂回式匹配追踪算法

df-traffic_sign_detect

基于虚拟仿真环境下的自动驾驶交通标志识别 Datafountain 平台上的一个竞赛，最终成绩为0.986,25th。前排大佬都能做到0.996+了，膜拜学习一下

dictionary-learning

dictol

DICTOL - A Dictionary Learning Toolbox in Matlab

dipdemo

《数字图像处理与机器视觉》书上的所有算法C++代码；在VS2013下测试，以MFC为交互界面，实现对输入图像的操作，涵盖了所有基本的图像处理算法，很值得学习！

dw-tnnr

This is an implementation of Double Weighted Truncated Nuclear Norm Regularization Method.

fpt

Implementation for paper Feature Pyramid Transformer

fptree

关联规则挖掘_Fptree算法

frsvt

I implemented the fllowing article by Matlab.Refrence:Oh T H, Matsushita Y, Tai Y W, et al. Fast Randomized Singular Value Thresholding for Low-rank Optimization[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2015, PP(99):1-1.Abstract:Rank minimization can be converted into tractable surrogate problems, such as Nuclear Norm Minimization (NNM) and Weighted NNM (WNNM). The problems related to NNM, or WNNM, can be solved iteratively by applying a closed-form proximal operator, called Singular Value Thresholding (SVT), or Weighted SVT, but they suffer from high computational cost of Singular Value Decomposition (SVD) at each iteration. We propose a fast and accurate approximation method for SVT, that we call fast randomized SVT (FRSVT), with which we avoid direct computation of SVD. The key idea is to extract an approximate basis for the range of the matrix from its compressed matrix. Given the basis, we compute partial singular values of the original matrix from the small factored matrix. In addition, by developping a range propagation method, our method further speeds up the extraction of approximate basis at each iteration. Our theoretical analysis shows the relationship between the approximation bound of SVD and its effect to NNM

fruit-recognition

OpenCV、C++、水果识别、Qt界面、颜色识别、边缘检测、图像处理

fsvt

fast randomized SVD and its application to SVT algorithm

fullstack-tutorial

🚀 fullstack tutorial 2020，后台技术栈/架构师之路/全栈开发社区，春招/秋招/校招/面试

gandenoising

gitskills

gms-feature-matcher

GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence (CVPR 17 & IJCV 20)

hasi

Hierarchical Adaptive Soft Impute

hello-world-1

my first repository

hello-world-2

just another repository