Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales

Terms and Conditions

Twitter GitHub LinkedIn Bluesky Youtube

© 2026 ResearchTrend.AI, All rights reserved.

Home
Papers
1604.03168
Cited By

Hardware-oriented Approximation of Convolutional Neural Networks

v1v2v3 (latest)

Hardware-oriented Approximation of Convolutional Neural Networks

11 April 2016

Mohammad Motamedi

ArXiv (abs)PDF HTML

Papers citing "Hardware-oriented Approximation of Convolutional Neural Networks"

24 / 74 papers shown

Low complexity convolutional neural network for vessel segmentation in
portable retinal diagnostic devices

Low complexity convolutional neural network for vessel segmentation in portable retinal diagnostic devices

M. Hajabdollahi

Reza Esfandiarpoor

S. M. Reza Soroushmehr

Kayvan Najarian

101

35

0

21 Feb 2018

Model compression via distillation and quantization

Model compression via distillation and quantization

Dan Alistarh

286

801

0

15 Feb 2018

On the Universal Approximability and Complexity Bounds of Quantized ReLU
Neural Networks

On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks

Jinjun Xiong

228

23

0

10 Feb 2018

Universal Deep Neural Network Compression

Universal Deep Neural Network Compression

Mostafa El-Khamy

260

90

0

07 Feb 2018

VIBNN: Hardware Acceleration of Bayesian Neural Networks

VIBNN: Hardware Acceleration of Bayesian Neural Networks

Caiwen Ding

204

96

0

02 Feb 2018

Tactics to Directly Map CNN graphs on Embedded FPGAs

Tactics to Directly Map CNN graphs on Embedded FPGAs

Jocelyn Sérot

Jocelyn Serot

85

64

0

20 Nov 2017

Improving Efficiency in Convolutional Neural Network with Multilinear
Filters

Improving Efficiency in Convolutional Neural Network with Multilinear Filters

Alexandros Iosifidis

244

43

0

28 Sep 2017

Deep Learning at 15PF: Supervised and Semi-Supervised Classification for
Scientific Data

Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data

Alexia Jolicoeur-Martineau

...

Mikhail Shiryaev

Srinivas Sridharan

186

84

0

17 Aug 2017

Towards lightweight convolutional neural networks for object detection

Towards lightweight convolutional neural networks for object detection

Dmitriy Anisimov

193

42

0

05 Jul 2017

Balanced Quantization: An Effective and Efficient Approach to Quantized
Neural Networks

Balanced Quantization: An Effective and Efficient Approach to Quantized Neural Networks

Shuchang Zhou

181

113

0

22 Jun 2017

ShiftCNN: Generalized Low-Precision Architecture for Inference of
Convolutional Neural Networks

ShiftCNN: Generalized Low-Precision Architecture for Inference of Convolutional Neural Networks

Denis A. Gudovskiy

191

59

0

07 Jun 2017

NullHop: A Flexible Convolutional Neural Network Accelerator Based on
Sparse Representations of Feature Maps

NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature MapsIEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2017

Alessandro Aimar

Enrico Calabrese

A. Rios-Navarro

Ricardo Tapiador-Morales

...

Moritz B. Milde

Federico Corradi

A. Linares-Barranco

295

255

0

05 Jun 2017

The High-Dimensional Geometry of Binary Neural Networks

The High-Dimensional Geometry of Binary Neural Networks

Alexander G. Anderson

173

79

0

19 May 2017

LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object
Detection in Embedded Systems

LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems

Subarna Tripathi

Byeongkeun Kang

Truong Thao Nguyen

171

37

0

16 May 2017

Hardware-Software Codesign of Accurate, Multiplier-free Deep Neural
Networks

Hardware-Software Codesign of Accurate, Multiplier-free Deep Neural Networks

194

74

0

11 May 2017

CBinfer: Change-Based Inference for Convolutional Neural Networks on
Video Data

CBinfer: Change-Based Inference for Convolutional Neural Networks on Video Data

Lukas Cavigelli

Luca Benini

186

52

0

14 Apr 2017

Efficient Processing of Deep Neural Networks: A Tutorial and Survey

Efficient Processing of Deep Neural Networks: A Tutorial and Survey

284

3,363

0

27 Mar 2017

Towards Closing the Energy Gap Between HOG and CNN Features for Embedded
Vision

Towards Closing the Energy Gap Between HOG and CNN Features for Embedded Vision

Amr Suleiman

122

58

0

17 Mar 2017

Deep Convolutional Neural Network Inference with Floating-point Weights
and Fixed-point Activations

Deep Convolutional Neural Network Inference with Floating-point Weights and Fixed-point Activations

141

88

0

08 Mar 2017

Hardware for Machine Learning: Challenges and Opportunities

Hardware for Machine Learning: Challenges and OpportunitiesIEEE Custom Integrated Circuits Conference (CICC), 2016

Amr Suleiman

Zhengdong Zhang

348

80

0

22 Dec 2016

Quantized Neural Networks: Training Neural Networks with Low Precision
Weights and Activations

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Matthieu Courbariaux

410

2,011

0

22 Sep 2016

Overcoming Challenges in Fixed Point Training of Deep Convolutional
Networks

Overcoming Challenges in Fixed Point Training of Deep Convolutional Networks

148

47

0

08 Jul 2016

YodaNN: An Architecture for Ultra-Low Power Binary-Weight CNN
Acceleration

YodaNN: An Architecture for Ultra-Low Power Binary-Weight CNN Acceleration

Lukas Cavigelli

Luca Benini

295

201

0

17 Jun 2016

Ristretto: Hardware-Oriented Approximation of Convolutional Neural
Networks

Ristretto: Hardware-Oriented Approximation of Convolutional Neural Networks

138

128

0

20 May 2016