On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance

On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance

25 March 2024

Emad Fallahzadeh

Ahmed E. Hassan

Papers citing "On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance"

9 / 9 papers shown

Title
Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey J. H. Liu Yao Du Kun Yang Yan Wang Xiping Hu Z. Wang Y. Liu Peng Sun Azzedine Boukerche Victor C.M. Leung 29 0 0 03 May 2025
On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance Jaskirat Singh Bram Adams Ahmed E. Hassan VLM 24 0 0 01 Nov 2024
An Empirical Study of Challenges in Converting Deep Learning Models Moses Openja Amin Nikanjam Ahmed Haj Yahmed Foutse Khomh Zhen Ming Zhengyong Jiang AAML 16 19 0 28 Jun 2022
Post-Training Sparsity-Aware Quantization Gil Shomron F. Gabbay Samer Kurzum U. Weiser MQ 15 32 0 23 May 2021
Single-Training Collaborative Object Detectors Adaptive to Bandwidth and Computation Juliano S. Assine José Cândido Silveira Santos Filho Eduardo Valle ObjD 34 7 0 03 May 2021
Split Computing for Complex Object Detectors: Challenges and Preliminary Results Yoshitomo Matsubara Marco Levorato 28 18 0 27 Jul 2020
Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence Shuiguang Deng Hailiang Zhao Weijia Fang Jianwei Yin Schahram Dustdar Albert Y. Zomaya 60 598 0 02 Sep 2019
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,106 0 16 Nov 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 279 39,083 0 01 Sep 2014