AAAI Publications, Thirty-Second AAAI Conference on Artificial Intelligence

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Democratization of Deep Learning Using DARVIZ
Anush Sankaran, Naveen Panwar, Shreya Khare, Senthil Mani, Akshay Sethi, Rahul Aralikatte, Neelamadhav Gantayat

Last modified: 2018-04-29


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.


Deep Learning; Research Paper Mining; DARVIZ

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