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Densely Connected Convolutional Networks by Chainer

This is an experimental implementation of Densely Connected Convolutional Networks using Chainer framework.

Requirements

Usage

Train a DenseNet on CIFAR-10 dataset using:

python code/train.py --gpu 0 -o result

Visualize training result using:

python code/visualize.py result/log -o result

Sample Result

img/training_loss.png

img/test_error.png

  • Model parameters: L = 40, k = 12
  • Batch size: 64
  • Dataset: C10 (CIFAR-10 dataset without data augmentation)