Web: http://arxiv.org/abs/2209.07282

Sept. 16, 2022, 1:12 a.m. | Jörg Christian Kirchhof, Evgeny Kusmenko, Jonas Ritz, Bernhard Rumpe, Armin Moin, Atta Badii, Stephan Günnemann, Moharram Challenger

cs.LG updates on arXiv.org arxiv.org

In this paper, we propose to adopt the MDE paradigm for the development of
Machine Learning (ML)-enabled software systems with a focus on the Internet of
Things (IoT) domain. We illustrate how two state-of-the-art open-source
modeling tools, namely MontiAnna and ML-Quadrat can be used for this purpose as
demonstrated through a case study. The case study illustrates using ML, in
particular deep Artificial Neural Networks (ANNs), for automated image
recognition of handwritten digits using the MNIST reference dataset, and
integrating …

arxiv case case study comparison machine machine learning software study systems

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