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Max-Pooling Dropout for Regularization of Convolutional Neural Networks

Max-Pooling Dropout for Regularization of Convolutional Neural Networks

Haibing Wu
Xiaodong Gu
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Papers citing "Max-Pooling Dropout for Regularization of Convolutional Neural Networks"

7 / 7 papers shown
Title
Virtual Underwater Datasets for Autonomous Inspections
Virtual Underwater Datasets for Autonomous Inspections
Ioannis Polymenis
M. Haroutunian
R. Norman
D. Trodden
19
7
0
13 Sep 2022
Improving Discrete Latent Representations With Differentiable Approximation Bridges
Improving Discrete Latent Representations With Differentiable Approximation Bridges
Jason Ramapuram
Russ Webb
DRL
19
9
0
09 May 2019
A Review of Meta-Reinforcement Learning for Deep Neural Networks Architecture Search
A Review of Meta-Reinforcement Learning for Deep Neural Networks Architecture Search
Yesmina Jaâfra
J. Laurent
A. Deruyver
M. Naceur
OOD
13
14
0
17 Dec 2018
Considerations for a PAP Smear Image Analysis System with CNN Features
Considerations for a PAP Smear Image Analysis System with CNN Features
Srishti Gautam
K. HarinarayanK.
Nirmal Jith
A. Sao
Arnav V. Bhavsar
A. Natarajan
31
33
0
23 Jun 2018
Deep Learning with Convolutional Neural Network for Objective Skill Evaluation in Robot-assisted Surgery
Deep Learning with Convolutional Neural Network for Objective Skill Evaluation in Robot-assisted Surgery
Ziheng Wang
A. M. Fey
27
216
0
15 Jun 2018
Towards Principled Design of Deep Convolutional Networks: Introducing SimpNet
Towards Principled Design of Deep Convolutional Networks: Introducing SimpNet
S. H. HasanPour
Mohammad Rouhani
Mohsen Fayyaz
Mohammad Sabokrou
Ehsan Adeli
50
45
0
17 Feb 2018
Improving neural networks by preventing co-adaptation of feature detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,640
0
03 Jul 2012