Democratization of Deep Learning Using DARVIZ

Anush Sankaran, Naveen Panwar, Shreya Khare, Senthil Mani, Akshay Sethi, Rahul Aralikatte, Neelamadhav Gantayat

AAAI 2018 pp. 8218-8219

doi:10.1609/AAAI.V32I1.11376 /aaai/2018/sankaran2018aaai-democratization/

Abstract

With an abundance of research papers in deep learning, adoption and reproducibility of existing works becomes a challenge. To make a DL developer life easy, we propose a novel system, DARVIZ, to visually design a DL model using a drag-and-drop framework in an platform agnostic manner. The code could be automatically generated in both Caffe and Keras. DARVIZ could import (i) any existing Caffe code, or (ii) a research paper containing a DL design; extract the design, and present it in visual editor.

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Cite

Text

Sankaran et al. "Democratization of Deep Learning Using DARVIZ." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.11376

Markdown

[Sankaran et al. "Democratization of Deep Learning Using DARVIZ." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/sankaran2018aaai-democratization/) doi:10.1609/AAAI.V32I1.11376

BibTeX

@inproceedings{sankaran2018aaai-democratization,
  title     = {{Democratization of Deep Learning Using DARVIZ}},
  author    = {Sankaran, Anush and Panwar, Naveen and Khare, Shreya and Mani, Senthil and Sethi, Akshay and Aralikatte, Rahul and Gantayat, Neelamadhav},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {8218-8219},
  doi       = {10.1609/AAAI.V32I1.11376},
  url       = {https://mlanthology.org/aaai/2018/sankaran2018aaai-democratization/}
}