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Intelligence Beyond the Edge: Inference on Intermittent Embedded Systems

Intelligence Beyond the Edge: Inference on Intermittent Embedded Systems

28 September 2018
Graham Gobieski
Nathan Beckmann
Brandon Lucia
ArXivPDFHTML

Papers citing "Intelligence Beyond the Edge: Inference on Intermittent Embedded Systems"

14 / 14 papers shown
Title
Revisiting DNN Training for Intermittently-Powered Energy-Harvesting Micro-Computers
Revisiting DNN Training for Intermittently-Powered Energy-Harvesting Micro-Computers
Cyan Subhra Mishra
Deeksha Chaudhary
Jack Sampson
Mahmut Taylan Knademir
Chita R. Das
45
0
0
28 Jan 2025
DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning
DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning
Lixiang Han
Zhen Xiao
Zhenjiang Li
43
5
0
17 Jan 2024
Real-time Neural Network Inference on Extremely Weak Devices: Agile
  Offloading with Explainable AI
Real-time Neural Network Inference on Extremely Weak Devices: Agile Offloading with Explainable AI
Kai Huang
Wei Gao
27
35
0
21 Dec 2023
Accuracy-Guaranteed Collaborative DNN Inference in Industrial IoT via
  Deep Reinforcement Learning
Accuracy-Guaranteed Collaborative DNN Inference in Industrial IoT via Deep Reinforcement Learning
Wen Wu
Peng Yang
Weiting Zhang
Conghao Zhou
Xuemin
X. Shen
24
103
0
31 Dec 2022
A Survey on Collaborative DNN Inference for Edge Intelligence
A Survey on Collaborative DNN Inference for Edge Intelligence
Weiqing Ren
Yuben Qu
Chao Dong
Yuqian Jing
Hao Sun
Qihui Wu
Song Guo
36
49
0
16 Jul 2022
EVE: Environmental Adaptive Neural Network Models for Low-power Energy
  Harvesting System
EVE: Environmental Adaptive Neural Network Models for Low-power Energy Harvesting System
Sahidul Islam
Shangli Zhou
Ran Ran
Yufang Jin
Wu-Shao Wen
Caiwen Ding
Mimi Xie
34
9
0
14 Jul 2022
Machine Learning for Microcontroller-Class Hardware: A Review
Machine Learning for Microcontroller-Class Hardware: A Review
Swapnil Sayan Saha
S. Sandha
Mani B. Srivastava
34
118
0
29 May 2022
Update Compression for Deep Neural Networks on the Edge
Update Compression for Deep Neural Networks on the Edge
Bo Chen
A. Bakhshi
Gustavo E. A. P. A. Batista
Brian Ng
Tat-Jun Chin
31
17
0
09 Mar 2022
AI for Next Generation Computing: Emerging Trends and Future Directions
AI for Next Generation Computing: Emerging Trends and Future Directions
S. Gill
Minxian Xu
Carlo Ottaviani
Panos Patros
Rami Bahsoon
...
R. Sakellariou
Schahram Dustdar
Omer F. Rana
Ivona Brandić
Steve Uhlig
25
391
0
05 Mar 2022
Towards Battery-Free Machine Learning and Inference in Underwater
  Environments
Towards Battery-Free Machine Learning and Inference in Underwater Environments
Yuchen Zhao
Sayed Saad Afzal
Waleed Akbar
Osvy Rodriguez
Fan Mo
David E. Boyle
Fadel M. Adib
Hamed Haddadi
3DV
27
19
0
16 Feb 2022
Towards Homomorphic Inference Beyond the Edge
Towards Homomorphic Inference Beyond the Edge
Salonik Resch
Z. Chowdhury
Husrev Cilasun
Masoud Zabihi
Zhengyang Zhao
Jianping Wang
S. Sapatnekar
Ulya R. Karpuzcu
16
1
0
10 Dec 2021
Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices
Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices
Sahidul Islam
Jieren Deng
Shangli Zhou
Chen Pan
Caiwen Ding
Mimi Xie
42
19
0
28 Nov 2021
Bringing AI To Edge: From Deep Learning's Perspective
Bringing AI To Edge: From Deep Learning's Perspective
Di Liu
Hao Kong
Xiangzhong Luo
Weichen Liu
Ravi Subramaniam
52
116
0
25 Nov 2020
ALERT: Accurate Learning for Energy and Timeliness
ALERT: Accurate Learning for Energy and Timeliness
Chengcheng Wan
M. Santriaji
E. Rogers
H. Hoffmann
Michael Maire
Shan Lu
AI4CE
48
40
0
31 Oct 2019
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