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This report provides an overview of the current state of the art deep learning architectures and optimisation techniques, and uses the ADNI hippocampus MRI dataset as an example to compare the effectiveness and efficiency of different convolutional architectures on the task of patch-based 3-dimensional hippocampal segmentation, which is important in the diagnosis of Alzheimer's Disease.
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Rprop-a fast adaptive learning algorithm
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Multilayer feedforward networks with a nonpolynomial activation function can approximate any function
Moshe Leshno, Vladimir Ya Lin, Allan Pinkus, and Shimon Schocken · 1993
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Learning long-term dependencies with gradient descent is difficult
Yoshua Bengio, Patrice Simard, and Paolo Frasconi · 1994
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Endel Tulving and Hans J Markowitsch · 1998
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A weight initialization method for improving training speed in feedforward neural network
Jim YF Yam and Tommy WS Chow · 2000
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Ensembling neural networks: many could be better than all
Zhi-Hua Zhou, Jianxin Wu, and Wei Tang · 2002
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Tuning of the structure and parameters of a neural network using an improved genetic algorithm
Frank Hung-Fat Leung, Hak-Keung Lam, Sai-Ho Ling, and Peter Kwong-Shun Tam · 2003
Cited alongside, same era.
A learning algorithm for evolving cascade neural networks
Vitaly Schetinin · 2003
Cited alongside, same era.
Atlas-based hippocampus segmentation in alzheimer’s disease and mild cognitive impairment
Owen T Carmichael, Howard A Aizenstein, Simon W Davis, James T Becker, Paul M Thompson, Carolyn Cidis Meltzer, and Yanxi Liu · 2005
Cited alongside, same era.
Model compression
Cristian Bucilua, Rich Caruana, and Alexandru Niculescu-Mizil · 2006
Theano: a cpu and gpu math expression compiler
James Bergstra, Olivier Breuleux, Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, Guillaume Desjardins, Joseph Turian, David Warde-Farley, and Yoshua Bengio · 2010
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Deep sparse rectifier networks
Xavier Glorot, Antoine Bordes, and Yoshua Bengio · 2011
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Traffic sign recognition with multi-scale convolutional networks
Pierre Sermanet and Yann LeCun · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan R Salakhutdinov · 2012
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Learning multiple layers of representation
Geoffrey E Hinton · 2007
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A unified architecture for natural language processing: Deep neural networks with multitask learning
Ronan Collobert and Jason Weston · 2008
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Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol · 2008
Cited alongside, same era.
Unsupervised feature learning for audio classification using convolutional deep belief networks
Honglak Lee, Peter Pham, Yan Largman, and Andrew Y Ng · 2009
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Deep machine learning-a new frontier in artificial intelligence research [research frontier]
Itamar Arel, Derek C Rose, and Thomas P Karnowski · 2010
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A theoretical analysis of feature pooling in visual recognition
Y-Lan Boureau, Jean Ponce, and Yann LeCun · 2010
Cited alongside, same era.
Matthew D Zeiler · 2012
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Representation learning: A review and new perspectives
Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2013
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Standardization of analysis sets for reporting results from adni mri data
Bradley T Wyman, Danielle J Harvey, Karen Crawford, Matt A Bernstein, Owen Carmichael, Patricia E Cole, Paul K Crane, Charles DeCarli, Nick C Fox, Jeffrey L Gunter, et al · 2013
Later among the works it cites.
Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network
Adhish Prasoon, Kersten Petersen, Christian Igel, François Lauze, Erik Dam, and Mads Nielsen · 2013
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Do deep nets really need to be deep?
Jimmy Ba and Rich Caruana · 2014
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A new 2.5 d representation for lymph node detection using random sets of deep convolutional neural network observations
Holger R Roth, Le Lu, Ari Seff, Kevin M Cherry, Joanne Hoffman, Shijun Wang, Jiamin Liu, Evrim Turkbey, and Ronald M Summers · 2014
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Encoding source language with convolutional neural network for machine translation
Fandong Meng, Zhengdong Lu, Mingxuan Wang, Hang Li, Wenbin Jiang, and Qun Liu · 2015
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