CEML: Mixing and moving complex event processing and machine learning to the edge of the network for IoT applications

By José Angel Carvajal Soto, Marc Jentsch, Davy Preuveneers, E. Zudor. 2016

29 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Dusist Niyato
2. Ala Al-Fuqaha
3. Victor C. M. Leung
4. Mohsen Guizani
5. Sameh Sorour
6. Xu Chen
7. Xueqiang Yan
8. Xiaofei Wang

In Signal Processing

1. Ala Al-Fuqaha
2. Victor C. M. Leung
3. Mohsen Guizani
4. Sameh Sorour
5. Dusist Niyato
6. M. Mohammadi

Citations in the corpus

• Deep Learning for IoT Big Data and Streaming Analytics: A Survey (2017, background): “, TensorFlow, Caffe, Torch and Theano) • Visualization tools • Longer training time compared to other tools [64], [65]”
• Convergence of Edge Computing and Deep Learning: A Comprehensive Survey (2019, background): “In [115], a framework, dealing with these chal-”