Visual Genealogy of Deep Neural Networks

@article{Wang2020VisualGO,
  title={Visual Genealogy of Deep Neural Networks},
  author={Qianwen Wang and Jun Yuan and Shuxin Chen and Hang Su and Huamin Qu and Shixia Liu},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  year={2020},
  volume={26},
  pages={3340-3352}
}
A comprehensive and comprehensible summary of existing deep neural networks (DNNs) helps practitioners understand the behaviour and evolution of DNNs, offers insights for architecture optimization, and sheds light on the working mechanisms of DNNs. However, this summary is hard to obtain because of the complexity and diversity of DNN architectures. To address this issue, we develop DNN Genealogy, an interactive visualization tool, to offer a visual summary of representative DNNs and their… Expand
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