Max-Pooling Dropout for Regularization of Convolutional Neural Networks

Max-Pooling Dropout for Regularization of Convolutional Neural Networks

4 December 2015

Xiaodong Gu

Papers citing "Max-Pooling Dropout for Regularization of Convolutional Neural Networks"

7 / 7 papers shown

Title
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 Jason Ramapuram Russ Webb DRL 19 9 0 09 May 2019
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 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 Ziheng Wang A. M. Fey 27 216 0 15 Jun 2018
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 Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,639 0 03 Jul 2012