您现在的位置:首页 > 教案模板 > 正文

时间序列应用分析 深度解读:深度学习在IoT大数据和流分析中的应用(9)

2018-02-26 10:03 网络整理 教案网

【17】W. Liu, J. Liu, X. Gu, K. Liu, X. Dai, and H. Ma, “Deep learning based intelligent basketball arena with energy image,” in International Conference on Multimedia Modeling. Springer, 2017, pp. 601–613.

【18】K.-C. Wang and R. Zemel, “classifying nba offensive plays using neural networks,” in Proc. MIT SLOAN Sports Analytics Conf, 2016.

【19】T. Kautz, B. H. Groh, J. Hannink, U. Jensen, H. Strubberg, and B. M. Eskofier, “Activity recognition in beach volleyball using a deep convolutional neural network,” Data Mining and Knowledge Discovery, pp. 1–28, 2017.

【20】M. S. Ibrahim, S. Muralidharan, Z. Deng, A. Vahdat, and G. Mori, “A hierarchical deep temporal model for group activity recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 1971–1980.

感谢蔡芳芳对本文的审校。

推荐:机器学习、大数据、深度学习、数据挖掘、统计、决策和风险分析、概率和模糊逻辑的常见问题解答

[机器学习、大数据、深度学习、数据挖掘、统计、决策和风险分析、概率和模糊逻辑的常见问题解答1、机器学习、大数据、深度学习、数据挖掘、统计、决策和风险分析、概率、模