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Deep Learning on Mobile Devices - A Review

Deep Learning on Mobile Devices - A Review

21 March 2019
Yunbin Deng
ArXivPDFHTML

Papers citing "Deep Learning on Mobile Devices - A Review"

11 / 11 papers shown
Title
Involution Fused ConvNet for Classifying Eye-Tracking Patterns of
  Children with Autism Spectrum Disorder
Involution Fused ConvNet for Classifying Eye-Tracking Patterns of Children with Autism Spectrum Disorder
Md. Farhadul Islam
Meem Arafat Manab
J. Mondal
Sarah Zabeen
Fardin Bin Rahman
Md. Zahidul Hasan
Farig Sadeque
Jannatun Noor
18
3
0
07 Jan 2024
Unveiling the frontiers of deep learning: innovations shaping diverse domains
Unveiling the frontiers of deep learning: innovations shaping diverse domains
Shams Forruque Ahmed
Md. Sakib Bin Alam
Maliha Kabir
Shaila Afrin
Sabiha Jannat Rafa
Aanushka Mehjabin
Amir H. Gandomi
AI4CE
42
2
0
06 Sep 2023
Towards Implementing Energy-aware Data-driven Intelligence for Smart
  Health Applications on Mobile Platforms
Towards Implementing Energy-aware Data-driven Intelligence for Smart Health Applications on Mobile Platforms
G. D. Samaraweera
Hung Nguyen
Hadi Zanddizari
Behnam Zeinali
Jerome Chang
30
0
0
01 Feb 2023
Defending with Errors: Approximate Computing for Robustness of Deep
  Neural Networks
Defending with Errors: Approximate Computing for Robustness of Deep Neural Networks
Amira Guesmi
Ihsen Alouani
Khaled N. Khasawneh
M. Baklouti
T. Frikha
Mohamed Abid
Nael B. Abu-Ghazaleh
AAML
OOD
30
2
0
02 Nov 2022
Estimating the Power Consumption of Heterogeneous Devices when
  performing AI Inference
Estimating the Power Consumption of Heterogeneous Devices when performing AI Inference
P. Machado
Ivica Matic
Francisco de Lemos
I. Ihianle
D. Adama
22
3
0
13 Jul 2022
Deep learning pipeline for image classification on mobile phones
Deep learning pipeline for image classification on mobile phones
Muhammad Muneeb
Samuel F. Feng
A. Henschel
MedIm
8
9
0
31 May 2022
Comfetch: Federated Learning of Large Networks on Constrained Clients
  via Sketching
Comfetch: Federated Learning of Large Networks on Constrained Clients via Sketching
Tahseen Rabbani
Brandon Yushan Feng
Marco Bornstein
Kyle Rui Sang
Yifan Yang
Arjun Rajkumar
A. Varshney
Furong Huang
FedML
59
2
0
17 Sep 2021
Smartphone Sensing for the Well-being of Young Adults: A Review
Smartphone Sensing for the Well-being of Young Adults: A Review
L. Meegahapola
D. Gática-Pérez
29
27
0
17 Dec 2020
Defensive Approximation: Securing CNNs using Approximate Computing
Defensive Approximation: Securing CNNs using Approximate Computing
Amira Guesmi
Ihsen Alouani
Khaled N. Khasawneh
M. Baklouti
T. Frikha
Mohamed Abid
Nael B. Abu-Ghazaleh
AAML
19
37
0
13 Jun 2020
Towards Unconstrained Palmprint Recognition on Consumer Devices: a
  Literature Review
Towards Unconstrained Palmprint Recognition on Consumer Devices: a Literature Review
Adrian-Stefan Ungureanu
S. Salahuddin
Peter Corcoran
34
31
0
02 Mar 2020
PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with
  Pattern-based Weight Pruning
PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning
Wei Niu
Xiaolong Ma
Sheng Lin
Shihao Wang
Xuehai Qian
X. Lin
Yanzhi Wang
Bin Ren
MQ
35
227
0
01 Jan 2020
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