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SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB
  model size

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

24 February 2016
F. Iandola
Song Han
Matthew W. Moskewicz
Khalid Ashraf
W. Dally
Kurt Keutzer
ArXivPDFHTML

Papers citing "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size"

19 / 819 papers shown
Title
PVANet: Lightweight Deep Neural Networks for Real-time Object Detection
PVANet: Lightweight Deep Neural Networks for Real-time Object Detection
Sanghoon Hong
Byungseok Roh
Kye-Hyeon Kim
Yeongjae Cheon
Minje Park
ObjD
26
82
0
23 Nov 2016
LCNN: Lookup-based Convolutional Neural Network
LCNN: Lookup-based Convolutional Neural Network
Hessam Bagherinezhad
Mohammad Rastegari
Ali Farhadi
13
89
0
20 Nov 2016
How to scale distributed deep learning?
How to scale distributed deep learning?
Peter H. Jin
Qiaochu Yuan
F. Iandola
Kurt Keutzer
3DH
27
136
0
14 Nov 2016
Bit-pragmatic Deep Neural Network Computing
Bit-pragmatic Deep Neural Network Computing
Jorge Albericio
Patrick Judd
A. Delmas
Sayeh Sharify
Andreas Moshovos
MQ
32
239
0
20 Oct 2016
Fused DNN: A deep neural network fusion approach to fast and robust
  pedestrian detection
Fused DNN: A deep neural network fusion approach to fast and robust pedestrian detection
Xianzhi Du
Mostafa El-Khamy
Jungwon Lee
L. Davis
22
274
0
11 Oct 2016
Adaptive Neuron Apoptosis for Accelerating Deep Learning on Large Scale
  Systems
Adaptive Neuron Apoptosis for Accelerating Deep Learning on Large Scale Systems
Charles Siegel
J. Daily
Abhinav Vishnu
AI4CE
16
10
0
03 Oct 2016
Distributed Training of Deep Neural Networks: Theoretical and Practical
  Limits of Parallel Scalability
Distributed Training of Deep Neural Networks: Theoretical and Practical Limits of Parallel Scalability
J. Keuper
Franz-Josef Pfreundt
GNN
55
97
0
22 Sep 2016
Pruning Filters for Efficient ConvNets
Pruning Filters for Efficient ConvNets
Hao Li
Asim Kadav
Igor Durdanovic
H. Samet
H. Graf
3DPC
63
3,659
0
31 Aug 2016
Local Binary Convolutional Neural Networks
Local Binary Convolutional Neural Networks
Felix Juefei Xu
Vishnu Boddeti
Marios Savvides
MQ
32
251
0
22 Aug 2016
Lets keep it simple, Using simple architectures to outperform deeper and
  more complex architectures
Lets keep it simple, Using simple architectures to outperform deeper and more complex architectures
S. H. HasanPour
Mohammad Rouhani
Mohsen Fayyaz
Mohammad Sabokrou
23
119
0
22 Aug 2016
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
Song Han
Jeff Pool
Sharan Narang
Huizi Mao
Enhao Gong
...
Peter Vajda
Manohar Paluri
J. Tran
Bryan Catanzaro
W. Dally
CVBM
27
83
0
15 Jul 2016
Compression of Neural Machine Translation Models via Pruning
Compression of Neural Machine Translation Models via Pruning
A. See
Minh-Thang Luong
Christopher D. Manning
MedIm
VLM
29
221
0
29 Jun 2016
Shallow Networks for High-Accuracy Road Object-Detection
Shallow Networks for High-Accuracy Road Object-Detection
Khalid Ashraf
Bichen Wu
F. Iandola
Matthew W. Moskewicz
Kurt Keutzer
ObjD
32
53
0
05 Jun 2016
FractalNet: Ultra-Deep Neural Networks without Residuals
FractalNet: Ultra-Deep Neural Networks without Residuals
Gustav Larsson
Michael Maire
Gregory Shakhnarovich
45
933
0
24 May 2016
Ristretto: Hardware-Oriented Approximation of Convolutional Neural
  Networks
Ristretto: Hardware-Oriented Approximation of Convolutional Neural Networks
Philipp Gysel
29
127
0
20 May 2016
Ternary Weight Networks
Ternary Weight Networks
Fengfu Li
Bin Liu
Xiaoxing Wang
Bo-Wen Zhang
Junchi Yan
MQ
38
521
0
16 May 2016
Training Constrained Deconvolutional Networks for Road Scene Semantic
  Segmentation
Training Constrained Deconvolutional Networks for Road Scene Semantic Segmentation
G. Ros
Simon Stent
P. Alcantarilla
Tomoki Watanabe
21
55
0
06 Apr 2016
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural
  Networks
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
Mohammad Rastegari
Vicente Ordonez
Joseph Redmon
Ali Farhadi
MQ
54
4,332
0
16 Mar 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained
  Quantization and Huffman Coding
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Song Han
Huizi Mao
W. Dally
3DGS
45
8,751
0
01 Oct 2015
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