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Xiaode Zhang's Projects

caffe icon caffe

Caffe: a fast open framework for deep learning.

caffe-fcn icon caffe-fcn

Run Long and Shelhamer's FCN image segmentation network using Caffe

caption_generator icon caption_generator

A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.

char-rnn icon char-rnn

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

chinese_ocr icon chinese_ocr

CTPN + DenseNet + CTC based end-to-end Chinese OCR implemented using tensorflow and keras

compcar_analysis icon compcar_analysis

Source code of some classification experiments evaluated on the newly published vehicle dataset CompCar

examples icon examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fcn.berkeleyvision.org icon fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

im2markup icon im2markup

Neural model for converting Image-to-Markup (by Yuntian Deng github.com/da03)

lfw_face_recognition_svm_ensemble icon lfw_face_recognition_svm_ensemble

LFW face recognition with svm and some ensemble methods,including Adaboost, Random Forest, Boosting, Voting and so on. PCA is used to extract features. Implemented with scikit-learn

pix2pix-tensorflow icon pix2pix-tensorflow

TensorFlow implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".

prefixtreeespan icon prefixtreeespan

The implement of the PrefixTreeESpan algorithm in paper "Lei Zou, Yansheng Lu, Huaming Zhang, Rong Hu: PrefixTreeESpan: A Pattern Growth Algorithm for Mining Embedded Subtrees. WISE 2006: 499-505." to mine frequent embedded substructure.

prml icon prml

PRML algorithms implemented in Python

seq2seq icon seq2seq

Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch

seqgan icon seqgan

A simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)

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