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Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

6 February 2015
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
    VLM
ArXiv (abs)PDFHTML

Papers citing "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification"

50 / 5,458 papers shown
Title
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
F. Iandola
Song Han
Matthew W. Moskewicz
Khalid Ashraf
W. Dally
Kurt Keutzer
187
7,513
0
24 Feb 2016
Revise Saturated Activation Functions
Revise Saturated Activation Functions
Bing Xu
Ruitong Huang
Mu Li
79
73
0
18 Feb 2016
Face Attribute Prediction Using Off-the-Shelf CNN Features
Face Attribute Prediction Using Off-the-Shelf CNN Features
Yang Zhong
Josephine Sullivan
Haibo Li
CVBM
101
102
0
12 Feb 2016
A Convolutional Attention Network for Extreme Summarization of Source
  Code
A Convolutional Attention Network for Extreme Summarization of Source Code
Miltiadis Allamanis
Hao Peng
Charles Sutton
AI4TS
90
585
0
09 Feb 2016
Practical Black-Box Attacks against Machine Learning
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
S. Jha
Z. Berkay Celik
A. Swami
MLAUAAML
87
3,690
0
08 Feb 2016
Disentangled Representations in Neural Models
Disentangled Representations in Neural Models
William F. Whitney
OODOCLDRL
130
18
0
07 Feb 2016
Leveraging Mid-Level Deep Representations For Predicting Face Attributes
  in the Wild
Leveraging Mid-Level Deep Representations For Predicting Face Attributes in the Wild
Yang Zhong
Josephine Sullivan
Haibo Li
3DHCVBM
99
43
0
04 Feb 2016
Unsupervised Regenerative Learning of Hierarchical Features in Spiking
  Deep Networks for Object Recognition
Unsupervised Regenerative Learning of Hierarchical Features in Spiking Deep Networks for Object Recognition
Priyadarshini Panda
Kaushik Roy
BDLSSL
73
104
0
03 Feb 2016
Hybrid CNN and Dictionary-Based Models for Scene Recognition and Domain
  Adaptation
Hybrid CNN and Dictionary-Based Models for Scene Recognition and Domain Adaptation
Guosen Xie
Xu-Yao Zhang
Shuicheng Yan
Cheng-Lin Liu
ObjD
81
150
0
29 Jan 2016
Unifying Adversarial Training Algorithms with Flexible Deep Data
  Gradient Regularization
Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization
Alexander Ororbia
C. Lee Giles
Daniel Kifer
OOD
81
24
0
26 Jan 2016
Hough-CNN: Deep Learning for Segmentation of Deep Brain Regions in MRI
  and Ultrasound
Hough-CNN: Deep Learning for Segmentation of Deep Brain Regions in MRI and Ultrasound
Fausto Milletari
Seyed-Ahmad Ahmadi
Christine Kroll
A. Plate
Verena E. Rozanski
...
J. Levin
O. Dietrich
B. Ertl-Wagner
K. Boetzel
Nassir Navab
246
365
0
26 Jan 2016
Survey on the attention based RNN model and its applications in computer
  vision
Survey on the attention based RNN model and its applications in computer vision
Feng Wang
David Tax
AI4TSAIMat
74
114
0
25 Jan 2016
A Taxonomy of Deep Convolutional Neural Nets for Computer Vision
A Taxonomy of Deep Convolutional Neural Nets for Computer Vision
Suraj Srinivas
Ravi Kiran Sarvadevabhatla
Konda Reddy Mopuri
N. Prabhu
S. Kruthiventi
R. Venkatesh Babu
OOD
69
216
0
25 Jan 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
89
23
0
23 Jan 2016
Deep Neural Networks predict Hierarchical Spatio-temporal Cortical
  Dynamics of Human Visual Object Recognition
Deep Neural Networks predict Hierarchical Spatio-temporal Cortical Dynamics of Human Visual Object Recognition
Radoslaw Martin Cichy
A. Khosla
D. Pantazis
Antonio Torralba
A. Oliva
3DH
60
70
0
12 Jan 2016
Recent Advances in Convolutional Neural Networks
Recent Advances in Convolutional Neural Networks
Jiuxiang Gu
Zhenhua Wang
Jason Kuen
Lianyang Ma
Amir Shahroudy
...
Xingxing Wang
Li Wang
Gang Wang
Jianfei Cai
Tsuhan Chen
260
5,263
0
22 Dec 2015
Deep Learning with S-shaped Rectified Linear Activation Units
Deep Learning with S-shaped Rectified Linear Activation Units
Xiaojie Jin
Chunyan Xu
Jiashi Feng
Yunchao Wei
Junjun Xiong
Shuicheng Yan
418
218
0
22 Dec 2015
Blockout: Dynamic Model Selection for Hierarchical Deep Networks
Blockout: Dynamic Model Selection for Hierarchical Deep Networks
Calvin Murdock
Zerui Li
Howard Zhou
Tom Duerig
OODBDL
77
47
0
16 Dec 2015
Instance-aware Semantic Segmentation via Multi-task Network Cascades
Instance-aware Semantic Segmentation via Multi-task Network Cascades
Jifeng Dai
Kaiming He
Jian Sun
SSeg
186
1,231
0
14 Dec 2015
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.4K
195,003
0
10 Dec 2015
Fine-grained Image Classification by Exploring Bipartite-Graph Labels
Fine-grained Image Classification by Exploring Bipartite-Graph Labels
Feng Zhou
Yuanqing Lin
90
131
0
08 Dec 2015
Direct Intrinsics: Learning Albedo-Shading Decomposition by
  Convolutional Regression
Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression
T. Narihira
Michael Maire
Stella X. Yu
120
185
0
08 Dec 2015
A Restricted Visual Turing Test for Deep Scene and Event Understanding
A Restricted Visual Turing Test for Deep Scene and Event Understanding
Qi
Tianfu Wu
M. Lee
Song-Chun Zhu
60
12
0
06 Dec 2015
What can we learn about CNNs from a large scale controlled object
  dataset?
What can we learn about CNNs from a large scale controlled object dataset?
Ali Borji
S. Izadi
Laurent Itti
32
5
0
04 Dec 2015
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DVBDL
892
27,479
0
02 Dec 2015
Loss Functions for Neural Networks for Image Processing
Loss Functions for Neural Networks for Image Processing
Hang Zhao
Orazio Gallo
I. Frosio
Jan Kautz
SupR
87
279
0
28 Nov 2015
Towards Automatic Image Editing: Learning to See another You
Towards Automatic Image Editing: Learning to See another You
Amir Ghodrati
Xu Jia
M. Pedersoli
Tinne Tuytelaars
GANCVBMOOD
59
37
0
26 Nov 2015
Natural Language Understanding with Distributed Representation
Natural Language Understanding with Distributed Representation
Kyunghyun Cho
GNNBDL
86
55
0
24 Nov 2015
LocNet: Improving Localization Accuracy for Object Detection
LocNet: Improving Localization Accuracy for Object Detection
Spyros Gidaris
N. Komodakis
ObjD
62
140
0
24 Nov 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
321
5,543
0
23 Nov 2015
Gradual DropIn of Layers to Train Very Deep Neural Networks
Gradual DropIn of Layers to Train Very Deep Neural Networks
L. Smith
Emily M. Hand
T. Doster
AI4CE
87
33
0
22 Nov 2015
Data-dependent Initializations of Convolutional Neural Networks
Data-dependent Initializations of Convolutional Neural Networks
Philipp Krahenbuhl
Carl Doersch
Jeff Donahue
Trevor Darrell
VLM
103
203
0
21 Nov 2015
Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural
  Nets
Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural Nets
T. Narihira
Damian Borth
Stella X. Yu
Karl S. Ni
Trevor Darrell
CoGe
28
14
0
21 Nov 2015
Adding Gradient Noise Improves Learning for Very Deep Networks
Adding Gradient Noise Improves Learning for Very Deep Networks
Arvind Neelakantan
Luke Vilnis
Quoc V. Le
Ilya Sutskever
Lukasz Kaiser
Karol Kurach
James Martens
AI4CEODL
85
545
0
21 Nov 2015
Training CNNs with Low-Rank Filters for Efficient Image Classification
Training CNNs with Low-Rank Filters for Efficient Image Classification
Yani Andrew Ioannou
D. Robertson
Jamie Shotton
R. Cipolla
A. Criminisi
95
152
0
20 Nov 2015
Multi-view 3D Models from Single Images with a Convolutional Network
Multi-view 3D Models from Single Images with a Convolutional Network
Maxim Tatarchenko
Alexey Dosovitskiy
Thomas Brox
3DV
163
382
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
124
895
0
20 Nov 2015
A convnet for non-maximum suppression
A convnet for non-maximum suppression
J. Hosang
Rodrigo Benenson
Bernt Schiele
74
76
0
19 Nov 2015
All you need is a good init
All you need is a good init
Dmytro Mishkin
Jirí Matas
ODL
127
612
0
19 Nov 2015
Deep Manifold Traversal: Changing Labels with Convolutional Features
Deep Manifold Traversal: Changing Labels with Convolutional Features
Jacob R. Gardner
P. Upchurch
Matt J. Kusner
Yixuan Li
Kilian Q. Weinberger
Kavita Bala
John E. Hopcroft
90
67
0
19 Nov 2015
Order-Embeddings of Images and Language
Order-Embeddings of Images and Language
Ivan Vendrov
Ryan Kiros
Sanja Fidler
R. Urtasun
128
548
0
19 Nov 2015
Conditional Computation in Neural Networks for faster models
Conditional Computation in Neural Networks for faster models
Emmanuel Bengio
Pierre-Luc Bacon
Joelle Pineau
Doina Precup
AI4CE
172
325
0
19 Nov 2015
Adjustable Bounded Rectifiers: Towards Deep Binary Representations
Adjustable Bounded Rectifiers: Towards Deep Binary Representations
Zhirong Wu
Dahua Lin
Xiaoou Tang
MQ
48
14
0
19 Nov 2015
Mediated Experts for Deep Convolutional Networks
Mediated Experts for Deep Convolutional Networks
Aykut Erdem
Winston H. Hsu
94
20
0
19 Nov 2015
Learning Neural Network Architectures using Backpropagation
Learning Neural Network Architectures using Backpropagation
Suraj Srinivas
R. Venkatesh Babu
AI4CE
77
30
0
17 Nov 2015
Jet-Images -- Deep Learning Edition
Jet-Images -- Deep Learning Edition
Luke de Oliveira
Michael Kagan
Lester W. Mackey
Benjamin Nachman
A. Schwartzman
PINN
74
311
0
16 Nov 2015
An Exploration of Softmax Alternatives Belonging to the Spherical Loss
  Family
An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family
A. D. Brébisson
Pascal Vincent
92
98
0
16 Nov 2015
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
Jiwon Kim
Jung Kwon Lee
Kyoung Mu Lee
SupR
132
6,210
0
14 Nov 2015
Deeply-Recursive Convolutional Network for Image Super-Resolution
Deeply-Recursive Convolutional Network for Image Super-Resolution
Jiwon Kim
Jung Kwon Lee
Kyoung Mu Lee
SupR
146
2,512
0
14 Nov 2015
Learning to Assign Orientations to Feature Points
Learning to Assign Orientations to Feature Points
K. M. Yi
Yannick Verdié
Pascal Fua
Vincent Lepetit
79
124
0
13 Nov 2015
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