chakkritte / CReLU

CReLU (Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units) with Caffe

CReLU (Concatenated Rectified Linear Units) with Caffe

CReLU (Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units)

By Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee

Paper : https://arxiv.org/pdf/1603.05201v2.pdf

If you use these models in your research, please cite:

@article{shang2016understanding,
  title={Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units},
  author={Shang, Wenling and Sohn, Kihyuk and Almeida, Diogo and Lee, Honglak},
  journal={arXiv preprint arXiv:1603.05201},
  year={2016}
}

Results

1-crop validation error on ImageNet (center 224x224 crop from resized image with shorter side=256):

model	top-1	top-5
AlexNet	42.8%	19.7%
SqueezeNet	42.5%	19.7%
CReLU (all) in paper	40.93%	19.39%
CReLU (conv1,4,7) in paper	40.45 %	18.58%
CReLU (conv1–4) in paper	39.82%	18.28%

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