stoneyang
I am a research engineer in the field of computer vision with an emphasize on deep-learning aspect.
Beijing, PR China
Pinned Repositories
caffe
Caffe: a fast open framework for deep learning.
opencv_contrib
Repository for OpenCV's extra modules
opencv
Open Source Computer Vision Library
caffe_ssd
Forked from Wei Liu's repository for SSD and ParseNet. For further information, please respectively refer to the original paper and the repository in README.md
caffe_ristretto
Forked version of Ristretto, for original version of Ristretto, see https://github.com/pmgysel/caffe
cv-arxiv-daily
🎓Automatically Update CV Papers Daily using Github Actions (Update Every 24th hours)
HDR_Toolbox
HDR Toolbox for processing High Dynamic Range (HDR) images into MATLAB and Octave
Multi-label-Inception-net
Multi-label image classification using pretrained Inception net.
NAS-Projects
Several neural architecture search (NAS) algorithms implemented in PyTorch.
tensorflow
Open source software library for numerical computation using data flow graphs.
stoneyang's Repositories
stoneyang/HDR_Toolbox
HDR Toolbox for processing High Dynamic Range (HDR) images into MATLAB and Octave
stoneyang/BinaryConnect
Training Deep Neural Networks with binary weights during propagations
stoneyang/BinaryNet
Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
stoneyang/BWN-XNOR-caffe
Binary Weight Network and XNOR Network.
stoneyang/Caffe-Python-Data-Layer
stoneyang/CaffeModelCompression
Tool to compress trained caffe weights
stoneyang/Deep-Compression-AlexNet
Deep Compression on AlexNet
stoneyang/dissertation
My dissertation
stoneyang/FPGA-Imaging-Library
An open source library for image processing on FPGA.
stoneyang/image_retrieval
Image retrieval system demo based on caffe and lsh
stoneyang/linmath.h
a lean linear math library, aimed at graphics programming. Supports vec3, vec4, mat4x4 and quaternions
stoneyang/LSTMVis
Visualization Toolbox for Long Short Term Memory networks (LSTMs)
stoneyang/py_img_seg_eval
Evaluation metrics for image segmentation inspired by paper Fully Convolutional Networks for Semantic Segmentation.
stoneyang/SqueezeNet-Deep-Compression
stoneyang/SqueezeNet-DSD-Training
Applying Dense-Sparse-Dense training methodology to SqueezeNet, DSD training improved the top-1 accuracy of SqueezeNet by 4.3% on ImageNet without changing the model architecture and model size.
stoneyang/stoneyang.github.io
my blog on github