Author:
Morariu Cristina,Răileanu Silviu,Borangiu Theodor,Anton Florin
Publisher
Springer International Publishing
Reference14 articles.
1. Arasu, A., et al.: STREAM: the Stanford data stream management system. In: Garofalakis, M., Gehrke, J., Rastogi, R. (eds.) Data Stream Management, pp. 317–336. Springer, Berlin (2016)
2. Kreps, J., Narkhede, N., Rao, J.: Kafka: a distributed messaging system for log processing. In: Proceedings of the NetDB, pp. 1–7 (2011)
3. Wang, J., Ma, Y., Zhang, L., Gao, R.X., Wu, D.: Deep learning for smart manufacturing: methods and applications. J. Manuf. Syst. (2018)
4. Shao, S.Y., Sun, W.J., Yan, R.Q., Wang, P., Gao, R.X.: A deep learning approach for fault diagnosis of induction motors in manufacturing. Chin. J. Mech. Eng. 30(6), 1347–1356 (2017)
5. LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015)
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