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Towards Collaborative Intelligence Friendly Architectures for Deep
  Learning

Towards Collaborative Intelligence Friendly Architectures for Deep Learning

1 February 2019
Amir Erfan Eshratifar
Amirhossein Esmaili
Massoud Pedram
ArXivPDFHTML

Papers citing "Towards Collaborative Intelligence Friendly Architectures for Deep Learning"

8 / 8 papers shown
Title
Deep Edge Intelligence: Architecture, Key Features, Enabling
  Technologies and Challenges
Deep Edge Intelligence: Architecture, Key Features, Enabling Technologies and Challenges
Prabath Abeysekara
Haipeng Dong
•. A. K. Qin
19
1
0
24 Oct 2022
Lightweight Compression of Intermediate Neural Network Features for
  Collaborative Intelligence
Lightweight Compression of Intermediate Neural Network Features for Collaborative Intelligence
R. Cohen
Hyomin Choi
Ivan V. Bajić
32
23
0
15 May 2021
Lightweight compression of neural network feature tensors for
  collaborative intelligence
Lightweight compression of neural network feature tensors for collaborative intelligence
R. Cohen
Hyomin Choi
Ivan V. Bajić
30
42
0
12 May 2021
Single-Training Collaborative Object Detectors Adaptive to Bandwidth and
  Computation
Single-Training Collaborative Object Detectors Adaptive to Bandwidth and Computation
Juliano S. Assine
José Cândido Silveira Santos Filho
Eduardo Valle
ObjD
55
8
0
03 May 2021
Pareto-Optimal Bit Allocation for Collaborative Intelligence
Pareto-Optimal Bit Allocation for Collaborative Intelligence
Saeed Ranjbar Alvar
Ivan V. Bajić
16
29
0
25 Sep 2020
Bit Allocation for Multi-Task Collaborative Intelligence
Bit Allocation for Multi-Task Collaborative Intelligence
Saeed Ranjbar Alvar
Ivan V. Bajić
24
25
0
14 Feb 2020
Back-and-Forth prediction for deep tensor compression
Back-and-Forth prediction for deep tensor compression
Hyomin Choi
R. Cohen
Ivan V. Bajić
16
28
0
14 Feb 2020
JointDNN: An Efficient Training and Inference Engine for Intelligent
  Mobile Cloud Computing Services
JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services
Amir Erfan Eshratifar
M. Abrishami
Massoud Pedram
FedML
34
248
0
25 Jan 2018
1