Open AccessSynthetic Data Generation for Deep Learning Models
Author(s) -
Christoph Petroll,
Martin Denk,
Jens Holtmannspötter,
Kristin Paetzold,
Philipp Höfer
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.35199/dfx2021.11
Subject(s) - metamodeling , computer science , set (abstract data type) , multidisciplinary design optimization , multidisciplinary approach , industrial engineering , quality (philosophy) , systems engineering , artificial intelligence , software engineering , engineering , programming language , social science , philosophy , epistemology , sociology