JohannesLipp / More-Machine-Learning-for-Less

Repository accompanying our research paper "More Machine Learning for Less: Comparing Data Generation Strategies in Mechanical Engineering and Manufacturing" presented at the 2019 IEEE Symposium Series on Computational Intelligence (SSCI) in Xiamen, China. Reference see https://publications.rwth-aachen.de/record/789814, PDF see https://www.researchgate.net/publication/337622933_More_Machine_Learning_for_Less_Comparing_Data_Generation_Strategies_in_Mechanical_Engineering_and_Manufacturing.

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More Machine Learning for Less

Repository accompanying our research paper "More Machine Learning for Less: Comparing Data Generation Strategies in Mechanical Engineering and Manufacturing" presented at the 2019 IEEE Symposium Series on Computational Intelligence (SSCI) in Xiamen, China. Reference see https://publications.rwth-aachen.de/record/789814, PDF see https://www.researchgate.net/publication/337622933_More_Machine_Learning_for_Less_Comparing_Data_Generation_Strategies_in_Mechanical_Engineering_and_Manufacturing. All Python code snippets are based on the datasets provided via data.7z

Authors: Vladimir Samsonov, Johannes Theissen-Lipp, Philipp Noodt, Alexia Fenollar Solvay, and Tobias Meisen.

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Repository accompanying our research paper "More Machine Learning for Less: Comparing Data Generation Strategies in Mechanical Engineering and Manufacturing" presented at the 2019 IEEE Symposium Series on Computational Intelligence (SSCI) in Xiamen, China. Reference see https://publications.rwth-aachen.de/record/789814, PDF see https://www.researchgate.net/publication/337622933_More_Machine_Learning_for_Less_Comparing_Data_Generation_Strategies_in_Mechanical_Engineering_and_Manufacturing.

License:GNU General Public License v3.0


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