Revision e1467a79dc6580ae009d827b5e6f274faff3b339 authored by liqunfu on 27 March 2020, 21:42:04 UTC, committed by GitHub on 27 March 2020, 21:42:04 UTC
support Pooling ops with Sequence axis
README.md
# CNTK Examples: Image/Classification/GoogLeNet
## 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 GoogLeNet (https://arxiv.org/abs/1409.4842) and its derivations for image classification.
|Network |Deep convolutional neural networks codenamed "Inception" (GoogLeNet).
|Training |See the details.
|Comments |See below.
## Running the example
### Getting the data
We use the ILSVRC2012 datasets to demonstrate how to train a GoogLeNet. GoogLeNet was initially published by Researchers at Google Inc., and it is fine-tuned to have excellent classification accuracy and low computation cost. It won first place in the [ILSVRC](http://www.image-net.org/challenges/LSVRC/) 2014 detection challenge.
ILSVRC2012 datasets are not included in the CNTK distribution. You may obtain it through http://image-net.org.
## Details
We currently offer the BN-Inception (https://arxiv.org/abs/1502.03167) and Inception V3 (https://arxiv.org/abs/1512.00567), Inception-ResNet-V1 (https://arxiv.org/abs/1602.07261) models.
### [BN-Inception](./BN-Inception)
### [Inception V3](./InceptionV3)
### [Inception-ResNet-V1](./Inception-ResNet-V1)
## Pre-trained Models
Pre-trained GoogLeNet models can be found [here](../../../../PretrainedModels/Image.md#googlenet).
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