Trading-off Accuracy and Energy of Deep Inference on Embedded Systems: A Co-Design Approach

29 January 2019

Papers citing "Trading-off Accuracy and Energy of Deep Inference on Embedded Systems: A Co-Design Approach"

5 / 5 papers shown

Title
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device Mario Almeida Stefanos Laskaridis Stylianos I. Venieris Ilias Leontiadis Nicholas D. Lane 17 36 0 20 Apr 2021
Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Co-design Cong Hao Jordan Dotzel Jinjun Xiong Luca Benini Zhiru Zhang Deming Chen 58 34 0 25 Mar 2021
SETGAN: Scale and Energy Trade-off GANs for Image Applications on Mobile Platforms Nitthilan Kanappan Jayakodi J. Doppa P. Pande GAN 30 4 0 23 Mar 2021
Enabling On-Device CNN Training by Self-Supervised Instance Filtering and Error Map Pruning Yawen Wu Zhepeng Wang Yiyu Shi Jiaxi Hu 16 44 0 07 Jul 2020
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights Aojun Zhou Anbang Yao Yiwen Guo Lin Xu Yurong Chen MQ 337 1,049 0 10 Feb 2017