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12306

12306智能刷票，订票

chineseocr_lite

超轻量级中文ocr，支持竖排文字识别, 支持ncnn推理 , psenet(8.5M) + crnn(6.3M) + anglenet(1.5M) 总模型仅17M

convolutions

Convolutions and transposed convolutions

docker-python

Kaggle Python docker image

dsd

DSD model zoo. Better accuracy models from DSD training on Imagenet with same model architecture

e200_opensource

The Ultra-Low Power RISC Core

faster-rcnn_tf

Faster-RCNN in Tensorflow

faster_rcnn

Faster R-CNN

fcn.berkeleyvision.org

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

fcn.tensorflow

Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)

forum

蓝灯(Lantern)官方论坛

git_learning

just for learning git skills

git_learning2

github-slideshow

A robot powered training repository :robot:

good-boy

just for fun 0.0

how-to-optimize-gemm

imagefeatures

A Library About The Image Features Extraction

kittiseg

A Kitti Road Segmentation model implemented in tensorflow.

mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

matconvnet

MatConvNet: CNNs for MATLAB

models

Models built with TensorFlow

multinet

Real-time Joint Semantic Reasoning for Autonomous Driving

ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

neural-style

Neural style in TensorFlow! :art:

nndl

Another Chinese Translation of Neural Networks and Deep Learning

panda-learning

学习强国 xuexiqiangguo 全网最好用学习强国助手：Panda_Learning 萌萌的熊猫帮你搞定学习强国

pixeldcn

Tensorflow Implementation of Pixel Deconvolutional Networks (PixelDCN and PixelDCL)

pynq-classification

Python on Zynq FPGA for Convolutional Neural Networks

residual-attention-convolutional-neural-network

It contains the Attention-56 and Attention-96 models built from scratch in keras. Residual Attention Networks are described in the paper "Residual Attention Network for Image Classification"(https://arxiv.org/pdf/1704.06904.pdf).