411-3
received master degree in school of computer science form the Xidian University, China, in 2018. Working in the Hikvision Research Institute.
Xidian Universityxian,shaanxi,china
Pinned Repositories
caffe
Caffe: a fast open framework for deep learning.
Class-segmentation-of-image-and-Object-Localization
Class Segmentation and Object Localization using superpixel neighbourhoods and crf
cnpy
cnpy lib,to read .npy file fastly
CppPrimer
:books: Solutions for C++ Primer 5th exercise answers.
crf
Conditional random fields package for images
CRF_Segmentation
DenseCRF_Made_For_Lib
densecrf modified to generate lib for superpixel-crf
PSP-CRF
Improving Semantic Image Segmentation with a Probabilistic Superpixel-based Dense Conditional Random Field
superpixel_densecrf
superpixel_densecrf:SLIC,extract features,crf,inference
superpixel_feature
extract superpixel_feature
411-3's Repositories
411-3/PSP-CRF
Improving Semantic Image Segmentation with a Probabilistic Superpixel-based Dense Conditional Random Field
411-3/superpixel_densecrf
superpixel_densecrf:SLIC,extract features,crf,inference
411-3/DenseCRF_Made_For_Lib
densecrf modified to generate lib for superpixel-crf
411-3/superpixel_feature
extract superpixel_feature
411-3/caffe
Caffe: a fast open framework for deep learning.
411-3/cnpy
cnpy lib,to read .npy file fastly
411-3/CppPrimer
:books: Solutions for C++ Primer 5th exercise answers.
411-3/crfasrnn_keras
CRF-RNN Keras/Tensorflow version
411-3/deeplab-public
Working copy of Deeplab repository
411-3/deeplearningbook-chinese
Deep Learning Book Chinese Translation
411-3/DenseCRF-1
411-3/fcn.berkeleyvision.org
Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.
411-3/fcnnpy_to_pixel
from fcn.npy[n*m] to generate pixel label
411-3/gbdt_lr
411-3/gcrf
Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs
411-3/kaggle-2014-criteo
411-3/lbp_make_lib
for image,to extract lbp features,and make to lib
411-3/MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
411-3/models
Models and examples built with TensorFlow
411-3/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
411-3/really-awesome-semantic-segmentation
A list of papers on Semantic Segmentation.
411-3/SLIC_Lib
slic on image to make lib
411-3/sshfs-win
SSHFS For Windows
411-3/tensorflow
Computation using data flow graphs for scalable machine learning
411-3/tensorflow-zh
谷歌全新开源人工智能系统TensorFlow官方文档中文版
411-3/test_lh
This is the first repository
411-3/tsa-contest-baseline
Some baselines for TSA Contest: http://algo.tpai.qq.com
411-3/upgmpp
Undirected Probailistic Graphical Modes for C++
411-3/vmaf
Perceptual video quality assessment based on multi-method fusion.
411-3/winfsp
Windows File System Proxy - FUSE for Windows