Corpus ID: 27973832

Wide and deep volumetric residual networks for volumetric image classification

@article{Arvind2017WideAD,
  title={Wide and deep volumetric residual networks for volumetric image classification},
  author={Varun Arvind and A. B. Costa and M. Badgeley and Samuel Cho and E. Oermann},
  journal={ArXiv},
  year={2017},
  volume={abs/1710.01217}
}

• Varun Arvind, A. B. Costa, +2 authors E. Oermann
• Published 2017
• Computer Science
• ArXiv

3D shape models that directly classify objects from 3D information have become more widely implementable. Current state of the art models rely on deep convolutional and inception models that are resource intensive. Residual neural networks have been demonstrated to be easier to optimize and do not suffer from vanishing/exploding gradients observed in deep networks. Here we implement a residual neural network for 3D object classification of the 3D Princeton ModelNet dataset. Further, we show… Expand

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