Fetching the paper…
Reading the bibliography…
Convolutional Neural Network (CNN) image classifiers are traditionally designed to have sequential convolutional layers with a single output layer.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner · 1998
Earlier work this paper cites.
Learning to forget: Continual prediction with lstm
F. A. Gers, J. Schmidhuber, and F. Cummins · 1999
Earlier work this paper cites.
Gradient flow in recurrent nets: the difficulty of learning long-term dependencies, 2001
S. Hochreiter, Y. Bengio, P. Frasconi, and J. Schmidhuber · 2001
Earlier work this paper cites.
Semantic hierarchies for visual object recognition
M. Marszalek and C. Schmid · 2007
Earlier work this paper cites.
Exploiting object hierarchy: Combining models from different category levels
A. Zweig and D. Weinshall · 2007
Earlier work this paper cites.
Constructing Category Hierarchies for Visual Recognition
M. Marszałek and C. Schmid · 2008
Earlier work this paper cites.
Learning multiple layers of features from tiny images
A. Krizhevsky and G. Hinton · 2009
Earlier work this paper cites.
Building and using a semantivisual image hierarchy
L. J. Li, C. Wang, Y. Lim, D. M. Blei, and L. Fei-Fei · 2010
Earlier work this paper cites.
Deep sparse rectifier neural networks
X. Glorot, A. Bordes, and Y. Bengio · 2011
Earlier work this paper cites.
Learning to share visual appearance for multiclass object detection
R. Salakhutdinov, A. Torralba, and J. Tenenbaum · 2011
Earlier work this paper cites.
Hierarchical image annotation using semantic hierarchies
H. Bannour and C. Hudelot · 2012
Earlier work this paper cites.
Improving neural networks by preventing co-adaptation of feature detectors
G. E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2012
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Cited alongside, same era.
Semantic hierarchies for image annotation: A survey
A.-M. Tousch, S. Herbin, and J.-Y. Audibert · 2012
Cited alongside, same era.
Learning hierarchical similarity metrics
N. Verma, D. Mahajan, S. Sellamanickam, and V. Nair · 2012
Cited alongside, same era.
Maxout Networks
I. J. Goodfellow, D. Warde-Farley, M. Mirza, A. Courville, and Y. Bengio · 2013
Cited alongside, same era.
Visual concept learning: Combining machine vision and bayesian generalization on concept hierarchies
Striving for simplicity: The all convolutional net
J. T. Springenberg, A. Dosovitskiy, T. Brox, and M. A. Riedmiller · 2014
Later among the works it cites.
Visualizing and Understanding Convolutional Networks
M. D. Zeiler and R. Fergus · 2014
Later among the works it cites.
Structured prediction energy networks
D. Belanger and A. McCallum · 2015
Later among the works it cites.
Fast and accurate deep network learning by exponential linear units (elus)
D. Clevert, T. Unterthiner, and S. Hochreiter · 2015
Later among the works it cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Y. Jia, J. T. Abbott, J. L. Austerweil, T. Griffiths, and T. Darrell · 2013
Cited alongside, same era.
M. Lin, Q. Chen, and S. Yan · 2013
Cited alongside, same era.
Overfeat: Integrated recognition, localization and detection using convolutional networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2013
Cited alongside, same era.
Discriminative transfer learning with tree-based priors
N. Srivastava and R. R. Salakhutdinov · 2013
Cited alongside, same era.
Stochastic pooling for regularization of deep convolutional neural networks
M. D. Zeiler and R. Fergus · 2013
Cited alongside, same era.
Large-Scale Object Classification Using Label Relation Graphs
J. Deng, N. Ding, Y. Jia, A. Frome, K. Murphy, S. Bengio, Y. Li, H. Neven, and H. Adam · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Later among the works it cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Later among the works it cites.
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree
C.-Y. Lee, P. W. Gallagher, and Z. Tu · 2015
Later among the works it cites.
D. Mishkin and J. Matas · 2015
Later among the works it cites.
ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
Later among the works it cites.
Hd-cnn: Hierarchical deep convolutional neural network for large scale visual recognition
Z. Yan, H. Zhang, R. Piramuthu, V. Jagadeesh, D. DeCoste, W. Di, and Y. Yu · 2015
Later among the works it cites.
L. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2016
Later among the works it cites.