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Network In Network

Network In Network

16 December 2013
Min Lin
Qiang Chen
Shuicheng Yan
ArXivPDFHTML

Papers citing "Network In Network"

50 / 755 papers shown
Title
SNN: Stacked Neural Networks
SNN: Stacked Neural Networks
Milad Mohammadi
Subhasis Das
21
15
0
27 May 2016
An Analysis of Deep Neural Network Models for Practical Applications
An Analysis of Deep Neural Network Models for Practical Applications
A. Canziani
Adam Paszke
Eugenio Culurciello
19
1,165
0
24 May 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
Learning a Metric Embedding for Face Recognition using the Multibatch
  Method
Learning a Metric Embedding for Face Recognition using the Multibatch Method
Oren Tadmor
Y. Wexler
Tal Rosenwein
Shai Shalev-Shwartz
Amnon Shashua
CVBM
32
53
0
24 May 2016
Measuring Neural Net Robustness with Constraints
Measuring Neural Net Robustness with Constraints
Osbert Bastani
Yani Andrew Ioannou
Leonidas Lampropoulos
Dimitrios Vytiniotis
A. Nori
A. Criminisi
AAML
25
422
0
24 May 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
98
7,920
0
23 May 2016
Swapout: Learning an ensemble of deep architectures
Swapout: Learning an ensemble of deep architectures
Saurabh Singh
Derek Hoiem
David A. Forsyth
BDL
3DPC
OOD
UQCV
23
150
0
20 May 2016
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks
Julien Mairal
SSL
34
130
0
20 May 2016
Ternary Weight Networks
Ternary Weight Networks
Fengfu Li
Bin Liu
Xiaoxing Wang
Bo Zhang
Junchi Yan
MQ
43
521
0
16 May 2016
ASP Vision: Optically Computing the First Layer of Convolutional Neural
  Networks using Angle Sensitive Pixels
ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels
H. G. Chen
Suren Jayasuriya
Jiyue Yang
J. Stephen
S. Sivaramakrishnan
Ashok Veeraraghavan
A. Molnar
26
66
0
11 May 2016
Structured Receptive Fields in CNNs
Structured Receptive Fields in CNNs
J. Jacobsen
Jan van Gemert
Zhongyu Lou
A. Smeulders
16
107
0
10 May 2016
DisturbLabel: Regularizing CNN on the Loss Layer
DisturbLabel: Regularizing CNN on the Loss Layer
Lingxi Xie
Jingdong Wang
Zhen Wei
Meng Wang
Qi Tian
41
250
0
30 Apr 2016
Novelty Detection in MultiClass Scenarios with Incomplete Set of Class
  Labels
Novelty Detection in MultiClass Scenarios with Incomplete Set of Class Labels
N. Vinokurov
D. Weinshall
26
4
0
21 Apr 2016
Deep CNNs for HEp-2 Cells Classification : A Cross-specimen Analysis
Deep CNNs for HEp-2 Cells Classification : A Cross-specimen Analysis
Hongwei Bran Li
Wei-Shi Zheng
Jianguo Zhang
30
15
0
20 Apr 2016
Deep Residual Networks with Exponential Linear Unit
Deep Residual Networks with Exponential Linear Unit
Anish Shah
Eashan Kadam
Hena Shah
Sameer Shinde
Sandip Shingade
50
120
0
14 Apr 2016
Volumetric and Multi-View CNNs for Object Classification on 3D Data
Volumetric and Multi-View CNNs for Object Classification on 3D Data
C. Qi
Hao Su
Matthias Niessner
Angela Dai
Mengyuan Yan
Leonidas J. Guibas
3DPC
3DV
66
1,561
0
12 Apr 2016
Using Deep Learning for Image-Based Plant Disease Detection
Using Deep Learning for Image-Based Plant Disease Detection
Sharada Mohanty
David P. Hughes
M. Salathé
15
3,043
0
11 Apr 2016
Multi-Bias Non-linear Activation in Deep Neural Networks
Multi-Bias Non-linear Activation in Deep Neural Networks
Hongyang Li
Wanli Ouyang
Xiaogang Wang
23
64
0
03 Apr 2016
Deep Networks with Stochastic Depth
Deep Networks with Stochastic Depth
Gao Huang
Yu Sun
Zhuang Liu
Daniel Sedra
Kilian Q. Weinberger
74
2,338
0
30 Mar 2016
Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for
  Automated Image Annotation
Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation
Hoo-Chang Shin
Kirk Roberts
Le Lu
Dina Demner-Fushman
Jianhua Yao
Ronald M. Summers
24
347
0
28 Mar 2016
Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing
Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing
S. K. Esser
P. Merolla
John V. Arthur
A. Cassidy
R. Appuswamy
...
Pallab Datta
A. Amir
B. Taba
M. Flickner
D. Modha
3DH
25
715
0
28 Mar 2016
Unsupervised Category Discovery via Looped Deep Pseudo-Task Optimization
  Using a Large Scale Radiology Image Database
Unsupervised Category Discovery via Looped Deep Pseudo-Task Optimization Using a Large Scale Radiology Image Database
Xiaosong Wang
Le Lu
Hoo-Chang Shin
Lauren Kim
Isabella Nogues
Jianhua Yao
Ronald M. Summers
22
16
0
25 Mar 2016
Attentive Contexts for Object Detection
Attentive Contexts for Object Detection
Jianan Li
Yunchao Wei
Xiaodan Liang
Jian Dong
Tingfa Xu
Jiashi Feng
Shuicheng Yan
ObjD
17
221
0
24 Mar 2016
Convolution in Convolution for Network in Network
Convolution in Convolution for Network in Network
Yanwei Pang
Manli Sun
Xiaoheng Jiang
Xuelong Li
34
167
0
22 Mar 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
75
4,332
0
16 Mar 2016
Understanding and Improving Convolutional Neural Networks via
  Concatenated Rectified Linear Units
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units
Wenling Shang
Kihyuk Sohn
Diogo Almeida
Honglak Lee
24
500
0
16 Mar 2016
Identity Mappings in Deep Residual Networks
Identity Mappings in Deep Residual Networks
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
135
10,127
0
16 Mar 2016
Network Morphism
Network Morphism
Tao Wei
Changhu Wang
Y. Rui
Chen Chen
21
176
0
05 Mar 2016
Normalization Propagation: A Parametric Technique for Removing Internal
  Covariate Shift in Deep Networks
Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks
Devansh Arpit
Yingbo Zhou
Bhargava U. Kota
V. Govindaraju
27
126
0
04 Mar 2016
Decision Forests, Convolutional Networks and the Models in-Between
Decision Forests, Convolutional Networks and the Models in-Between
Yani Andrew Ioannou
D. Robertson
Darko Zikic
Peter Kontschieder
Jamie Shotton
Matthew Brown
A. Criminisi
26
88
0
03 Mar 2016
Cascaded Subpatch Networks for Effective CNNs
Cascaded Subpatch Networks for Effective CNNs
Xiaoheng Jiang
Yanwei Pang
Manli Sun
Xuelong Li
34
39
0
01 Mar 2016
Weight Normalization: A Simple Reparameterization to Accelerate Training
  of Deep Neural Networks
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
Tim Salimans
Diederik P. Kingma
ODL
111
1,926
0
25 Feb 2016
Automatic Moth Detection from Trap Images for Pest Management
Automatic Moth Detection from Trap Images for Pest Management
Weiguang Ding
Graham W. Taylor
12
305
0
24 Feb 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on
  Learning
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
Sergey Ioffe
Vincent Vanhoucke
Alexander A. Alemi
179
14,151
0
23 Feb 2016
Correlation Hashing Network for Efficient Cross-Modal Retrieval
Correlation Hashing Network for Efficient Cross-Modal Retrieval
Yue Cao
Mingsheng Long
Jianmin Wang
Philip S. Yu
21
59
0
22 Feb 2016
Binarized Neural Networks
Itay Hubara
Daniel Soudry
Ran El-Yaniv
MQ
58
1,350
0
08 Feb 2016
Learning scale-variant and scale-invariant features for deep image
  classification
Learning scale-variant and scale-invariant features for deep image classification
Nanne van Noord
E. Postma
SSL
19
157
0
03 Feb 2016
Automatic recognition of element classes and boundaries in the birdsong
  with variable sequences
Automatic recognition of element classes and boundaries in the birdsong with variable sequences
Takuya Koumura
K. Okanoya
35
23
0
23 Jan 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural
  Networks
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks
Chunyuan Li
Changyou Chen
David Carlson
Lawrence Carin
ODL
BDL
29
320
0
23 Dec 2015
A Deep Generative Deconvolutional Image Model
A Deep Generative Deconvolutional Image Model
Yunchen Pu
Xin Yuan
Andrew Stevens
Chunyuan Li
Lawrence Carin
BDL
VLM
32
44
0
23 Dec 2015
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
473
191,646
0
10 Dec 2015
Towards Dropout Training for Convolutional Neural Networks
Towards Dropout Training for Convolutional Neural Networks
Haibing Wu
Xiaodong Gu
35
299
0
01 Dec 2015
Fast and Accurate Deep Network Learning by Exponential Linear Units
  (ELUs)
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
Djork-Arné Clevert
Thomas Unterthiner
Sepp Hochreiter
126
5,494
0
23 Nov 2015
ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation
ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation
Francesco Visin
Marco Ciccone
Adriana Romero
Kyle Kastner
Kyunghyun Cho
Yoshua Bengio
Matteo Matteucci
Aaron Courville
VLM
SSeg
19
251
0
22 Nov 2015
Superpixel Convolutional Networks using Bilateral Inceptions
Superpixel Convolutional Networks using Bilateral Inceptions
Raghudeep Gadde
Varun Jampani
Martin Kiefel
Daniel Kappler
Peter V. Gehler
SSeg
SupR
32
129
0
20 Nov 2015
Hand Pose Estimation through Semi-Supervised and Weakly-Supervised
  Learning
Hand Pose Estimation through Semi-Supervised and Weakly-Supervised Learning
Natalia Neverova
Christian Wolf
Florian Nebout
Graham W. Taylor
MDE
3DH
20
47
0
20 Nov 2015
Compression of Deep Convolutional Neural Networks for Fast and Low Power
  Mobile Applications
Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications
Yong-Deok Kim
Eunhyeok Park
S. Yoo
Taelim Choi
Lu Yang
Dongjun Shin
40
891
0
20 Nov 2015
On the energy landscape of deep networks
On the energy landscape of deep networks
Pratik Chaudhari
Stefano Soatto
ODL
43
27
0
20 Nov 2015
Learning to decompose for object detection and instance segmentation
Learning to decompose for object detection and instance segmentation
Eunbyung Park
Alexander C. Berg
30
23
0
19 Nov 2015
Why M Heads are Better than One: Training a Diverse Ensemble of Deep
  Networks
Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks
Stefan Lee
Senthil Purushwalkam
Michael Cogswell
David J. Crandall
Dhruv Batra
FedML
UQCV
22
309
0
19 Nov 2015
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