Evolutionary Design of Reduced Precision Preprocessor for Levodopa-Induced Dyskinesia Classifier
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Springer International Publishing
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https://link.springer.com/content/pdf/10.1007/978-3-031-14714-2_34
Reference11 articles.
1. Drahosova, M., Sekanina, L., Wiglasz, M.: Adaptive fitness predictors in coevolutionary cartesian genetic programming. Evol. Comput. 27(3), 497–523 (2019). https://doi.org/10.1162/evco_a_00229
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3. Hurta, M., Drahosova, M., Sekanina, L., Smith, S.L., Alty, J.E.: Evolutionary design of reduced precision levodopa-induced dyskinesia classifiers. In: Medvet, E., Pappa, G., Xue, B. (eds.) EuroGP 2022: Proceedings of the 25th European Conference on Genetic Programming, LNCS, pp. 85–101. Springer Verlag, Madrid (2022). https://doi.org/10.1007/978-3-031-02056-8_6
4. Lones, M.A., et al.: A new evolutionary algorithm-based home monitoring device for Parkinson’s dyskinesia. J. Med. Syst. 41(11), 1–8 (2017). https://doi.org/10.1007/s10916-017-0811-7
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Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. MODEE-LID: Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers;2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS);2023-05-03
2. ADEE-LID: Automated Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers;2023 Design, Automation & Test in Europe Conference & Exhibition (DATE);2023-04
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