TY - JOUR AU - Sankaran, Anush AU - Panwar, Naveen AU - Khare, Shreya AU - Mani, Senthil AU - Sethi, Akshay AU - Aralikatte, Rahul AU - Gantayat, Neelamadhav PY - 2018/04/29 Y2 - 2024/03/28 TI - Democratization of Deep Learning Using DARVIZ JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 32 IS - 1 SE - Demonstrations DO - 10.1609/aaai.v32i1.11376 UR - https://ojs.aaai.org/index.php/AAAI/article/view/11376 SP - AB - <p> 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. </p> ER -