DeePar: A hybrid device-edge-cloud execution framework for mobile deep learning applications

Y Huang, F Wang, F Wang, J Liu - IEEE INFOCOM 2019-IEEE …, 2019 - ieeexplore.ieee.org
With the deep penetration of mobile devices, more and more mobile deep learning
applications have been widely used in daily life. However, since deep learning tasks are …
被引用次数：41 相关文章
[PDF] sfu.ca

[PDF][PDF] DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile Deep Learning Applications

Y Huang, F Wang, F Wang, J Liu - sfu.ca
With the deep penetration of mobile devices, more and more mobile deep learning
applications have been widely used in daily life. However, since deep learning tasks are …
[PDF] semanticscholar.org

[PDF][PDF] DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile Deep Learning Applications

Y Huang, F Wang, F Wang, J Liu - 2019 - pdfs.semanticscholar.org
DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile Deep Learning
Applications Page 1 DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile …
[PDF] comsoc.org

[PDF][PDF] DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile Deep Learning Applications

Y Huang, F Wang, F Wang, J Liu - 2019 - ni.committees.comsoc.org
DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile Deep Learning
Applications Page 1 DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile …
[PDF] sfu.ca

[PDF][PDF] DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile Deep Learning Applications

Y Huang, F Wang, F Wang, J Liu - sfu.ca
With the deep penetration of mobile devices, more and more mobile deep learning
applications have been widely used in daily life. However, since deep learning tasks are …