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LogAvgExp Provides a Principled and Performant Global Pooling Operator

LogAvgExp Provides a Principled and Performant Global Pooling Operator

2 November 2021
S. Lowe
Thomas Trappenberg
Sageev Oore
    FAtt
ArXiv (abs)PDFHTML

Papers citing "LogAvgExp Provides a Principled and Performant Global Pooling Operator"

21 / 21 papers shown
Title
Mish: A Self Regularized Non-Monotonic Activation Function
Mish: A Self Regularized Non-Monotonic Activation Function
Diganta Misra
71
679
0
23 Aug 2019
On the Variance of the Adaptive Learning Rate and Beyond
On the Variance of the Adaptive Learning Rate and Beyond
Liyuan Liu
Haoming Jiang
Pengcheng He
Weizhu Chen
Xiaodong Liu
Jianfeng Gao
Jiawei Han
ODL
289
1,906
0
08 Aug 2019
Bag of Tricks for Image Classification with Convolutional Neural
  Networks
Bag of Tricks for Image Classification with Convolutional Neural Networks
Tong He
Zhi-Li Zhang
Hang Zhang
Zhongyue Zhang
Junyuan Xie
Mu Li
284
1,419
0
04 Dec 2018
AutoAugment: Learning Augmentation Policies from Data
AutoAugment: Learning Augmentation Policies from Data
E. D. Cubuk
Barret Zoph
Dandelion Mané
Vijay Vasudevan
Quoc V. Le
131
1,774
0
24 May 2018
Self-Attention Generative Adversarial Networks
Self-Attention Generative Adversarial Networks
Han Zhang
Ian Goodfellow
Dimitris N. Metaxas
Augustus Odena
GAN
148
3,729
0
21 May 2018
Detail-Preserving Pooling in Deep Networks
Detail-Preserving Pooling in Deep Networks
Faraz Saeedan
Nicolas Weber
Michael Goesele
Stefan Roth
92
91
0
11 Apr 2018
Fix your classifier: the marginal value of training the last weight
  layer
Fix your classifier: the marginal value of training the last weight layer
Elad Hoffer
Itay Hubara
Daniel Soudry
134
102
0
14 Jan 2018
Fine-tuning CNN Image Retrieval with No Human Annotation
Fine-tuning CNN Image Retrieval with No Human Annotation
Filip Radenovic
Giorgos Tolias
Ondřej Chum
84
1,307
0
03 Nov 2017
Squeeze-and-Excitation Networks
Squeeze-and-Excitation Networks
Jie Hu
Li Shen
Samuel Albanie
Gang Sun
Enhua Wu
424
26,539
0
05 Sep 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
1.2K
20,858
0
17 Apr 2017
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Zhuowen Tu
Kaiming He
522
10,345
0
16 Nov 2016
Deep Pyramidal Residual Networks
Deep Pyramidal Residual Networks
Dongyoon Han
Jiwhan Kim
Junmo Kim
98
694
0
10 Oct 2016
Revisiting Multiple Instance Neural Networks
Revisiting Multiple Instance Neural Networks
Xinggang Wang
Yongluan Yan
Peng Tang
X. Bai
Wenyu Liu
115
446
0
08 Oct 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN3DV
775
36,861
0
25 Aug 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
349
7,995
0
23 May 2016
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image
  Segmentation
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation
Alexander Kolesnikov
Christoph H. Lampert
SSeg
52
747
0
19 Mar 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,322
0
10 Dec 2015
Deep SimNets
Deep SimNets
Nadav Cohen
Or Sharir
Amnon Shashua
69
46
0
09 Jun 2015
Fractional Max-Pooling
Fractional Max-Pooling
Benjamin Graham
TPM
98
517
0
18 Dec 2014
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
480
43,685
0
17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,479
0
04 Sep 2014
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