Deep learning on mobile and embedded devices: State-of-the-art, challenges, and future directions
Recent years have witnessed an exponential increase in the use of mobile and embedded
devices. With the great success of deep learning in many fields, there is an emerging trend …
devices. With the great success of deep learning in many fields, there is an emerging trend …
[PDF][PDF] Deep learning on mobile and embedded devices: State-of-the-art, challenges, and future directions
Y Chen, B Zheng, Z Zhang, Q Wang… - ACM Computing …, 2020 - drive.google.com
Recent years have witnessed the rapid development of deep learning with successful
applications in a wide range of areas, including image classification [91, 169], speech …
applications in a wide range of areas, including image classification [91, 169], speech …
Deep Learning on Mobile and Embedded Devices: State-of-the-art, Challenges, and Future Directions
Y Chen, B Zheng, Z Zhang, Q Wang… - ACM Computing …, 2020 - repository.ust.hk
Recent years have witnessed an exponential increase in the use of mobile and embedded
devices. With the great success of deep learning in many fields, there is an emerging trend …
devices. With the great success of deep learning in many fields, there is an emerging trend …
[PDF][PDF] Deep Learning on Mobile and Embedded Devices: State-of-the-art, Challenges, and Future Directions
Y CHEN, B ZHENG, Z ZHANG, Q WANG - 2020 - drive.google.com
Recent years have witnessed the rapid development of deep learning with successful
applications in a wide range of areas, including image classification [91, 169], speech …
applications in a wide range of areas, including image classification [91, 169], speech …