yuanhaogong Goto Github PK

30min_guides

覃健祥的学习笔记，各种几十分钟入门的文档

acnn

Code for the paper "Learning shape correspondence with anisotropic convolutional neural networks"

adaptiveoptim

Adaptive optimization procedure

aetros-cli

Python library to manage/monitor deep neural network training in AETROS Trainer

arrayfire

ArrayFire: a general purpose GPU library.

astra-toolbox

ASTRA Tomography Toolbox

auglagl1

A New Augmented Lagrangian Approach for L¹-mean Curvature Image Denoising

awesome-matlab

A curated list of awesome MATLAB toolboxes, applications, software and resources.

awesome-random-forest

Random Forest - a curated list of resources regarding random forest

bluebottle-3.0

A many-GPU-centric two phase flow simulation code implementing the Physalis method

caffe-lowlevel

Project for paper "Learning Recursive Filters for Low-Level Vision via a Hybrid Neural Network", ECCV 2016

cd-fer-benchmark

Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition (AGRA, ACM 2020, Oral)

celex5-mipi

SDK for CeleX5 sensor on CX3 platform.

cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers

cluster

cnn-fpga

使用Verilog实现的CNN模块，可以方便的在FPGA项目中使用

coma

Convolutional Mesh Autoencoders for Generating 3D Faces

conv-net-version-3

Deep neural network framework (C++/OpenCV).

cpp_concurrency_in_action

:book: 作为对《C++ Concurrency in Action》英文版的中文翻译。

curvaturefilter

Curvature Filters are efficient solvers for Variational Models

cvpr16_deblur_study

cvpr2016

Learning Deep Representations of Fine-grained Visual Descriptions

cvpr2016_stylenet

Code for our CVPR 2016 paper on Fashion styles in 128 floats.

cvui

A (very) simple UI lib built on top of OpenCV drawing primitives

deep-admm-net

基于深度神经网络的ADMM算法研究

deep-mri-reconstruction

Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction: Implementation & Demo

deeplearning

Deep Learning (Python, C, C++, Java, Scala, Go)

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.

deepskeleton

:racehorse:code for cvpr2016 paper "Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs"

densenet

DenseNet implementation in Keras