https://github.com/Microsoft/CNTK
Raw File
Tip revision: 5d14950684bda6f8ea64984b52dd9fbd6387e77f authored by Eldar Akchurin on 01 March 2017, 14:17:46 UTC
Implementation of sparse labels
Tip revision: 5d14950
README.md
# CNTK Examples: Image/Classification/VGG

## Overview

|Data:     |The ILSVRC2012 dataset (http://www.image-net.org/challenges/LSVRC/2012/) for image classification.
|:---------|:---
|Purpose   |This folder contains examples that demonstrate how to use CNTK to define VGG network (https://arxiv.org/abs/1409.1556) for image classification.
|Network   |VGG.
|Training  |Stochastic gradient descent with momentum.
|Comments  |See below.

## Running the example

### Getting the data
We use the ILSVRC2012 datasets to demonstrate how to train the VGG model which was developed by the [Visual Geometry Group in University of Oxford](http://www.robots.ox.ac.uk/~vgg/research/very_deep/). It won the second place in the ILSVRC-2014 challenge. VGG has been a very popular model for its simple architect and high accuracy. 

ILSVRC2012 datasets are not included in the CNTK distribution. You may obtain it through http://image-net.org.

## Details

We give examples for both Python and BrainScript.

### [Python](./Python)

### [BrainScript](./BrainScript)
back to top