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asap-sas

Sample code for the short answer scoring contest, hosted by Kaggle

awesome-deep-learning-papers

The most cited deep learning papers

awesome-ocr

Links to awesome OCR projects

awesome-random-forest

Random Forest - a curated list of resources regarding random forest

awesome-scene-text-recognition

A curated list of resources dedicated to scene text localization and recognition

captcha

Breaking captchas using torch

captcha-decoder

carnd-behavioral-cloning

carnd-behavioral-cloning-p3

Starting files for the Udacity CarND Behavioral Cloning Project

carnd-term1-starter-kit

cnn-lstm-ctc-text-recognition

CNN and LSTM model for text recognition

cnn-text-classification-tf

Convolutional Neural Network for Text Classification in Tensorflow

coarse-discourse

convnet-benchmarks

Easy benchmarking of all publicly accessible implementations of convnets

crnn

Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.

ctpn

Detecting Text in Natural Image with Connectionist Text Proposal Network

ctpn_xl

for new opencv, rewrite with matplotlib

curated-scene-text-recognition-analysis

Curated lists of scene text recognition and analysis

darknet

Convolutional Neural Networks

deep_learning

Deep Learning Resources and Tutorials using Keras and Lasagne

deepcut-cnn

CNN architecture for articulated human pose estimation

deeplearning.scala

A DSL for creating complex neural networks

dl_tutorials

Deep learning tutorials (2nd ed.)

dlbench

Benchmarking State-of-the-Art Deep Learning Software Tools

docker-stacks

Opinionated stacks of ready-to-run Jupyter applications in Docker.

ekho

Chinese text-to-speech engine

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit

five-video-classification-methods

Code that accompanies my blog post outlining five video classification methods in Keras and TensorFlow

fnlp

中文自然语言处理工具包 Toolkit for Chinese natural language processing

gan-sandbox

Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.