Fetching the paper…
Reading the bibliography…
We present a fast, fully parameterizable GPU implementation of Convolutional Neural Network variants.
Receptive fields of single neurones in the cat’s striate cortex
D. H. Wiesel and T. N. Hubel · 1959
Earlier work this paper cites.
Neocognitron: A self-organizing neural network for a mechanism of pattern recognition unaffected by shift in position
K. Fukushima · 1980
Earlier work this paper cites.
Learning factorial codes by predictability minimization
J. Schmidhuber · 1992
Earlier work this paper cites.
Semilinear predictability minimization produces well-known feature detectors
J. Schmidhuber, M. Eldracher, and B. Foltin · 1996
Earlier work this paper cites.
Sparse coding with an overcomplete basis set: A strategy employed by v1?
B. A. Olshausen and D. J. Field · 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.
Hierarchical models of object recognition in cortex
M. Riesenhuber and T. Poggio · 1999
Earlier work this paper cites.
Independent component analysis applied to feature extraction from colour and stero images
P. O. Hoyer and A. Hyvärinen · 2000
Earlier work this paper cites.
Hierarchical Neural Networks for Image Interpretation
S. Behnke · 2003
Cited alongside, same era.
Neocognitron for handwritten digit recognition
K. Fukushima · 2003
Cited alongside, same era.
Best practices for convolutional neural networks applied to visual document analysis
P. Simard, D. Steinkraus, and J. Platt · 2003
Cited alongside, same era.
Learning methods for generic object recognition with invariance to pose and lighting
Y. LeCun, F.-J. Huang, and L. Bottou · 2004
Cited alongside, same era.
High performance convolutional neural networks for document processing
K. Chellapilla, S. Puri, and P. Simard · 2006
Cited alongside, same era.
Object recognition with features inspired by visual cortex
T. Serre, L. Wolf, and T. Poggio · 2007
Cited alongside, same era.
3d object recognition with deep belief nets
V. Nair and G. E. Hinton · 2009
Later among the works it cites.
A high-throughput screening approach to discovering good forms of biologically inspired visual representation
N. Pinto, D. Doukhan, J. J. DiCarlo, and D. D. Cox · 2009
Later among the works it cites.
Large-scale object recognition with cuda-accelerated hierarchical neural networks
R. Uetz and S. Behnke · 2009
Later among the works it cites.
Deep big simple neural nets for handwritten digit recogntion
D. C. Cireşan, U. Meier, L. M. Gambardella, and J. Schmidhuber · 2010
Later among the works it cites.
An analysis of single-layer networks in unsupervised feature learning
A. Coates, H. Lee, and A. Ng · 2010
Later among the works it cites.
Evaluation of pooling operations in convolutional architectures for object recognition
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Object class recognition and localization using sparse features with limited receptive fields
J. Mutch and D. G. Lowe · 2008
Cited alongside, same era.
Learning multiple layers of features from tiny images
A. Krizhevsky · 2009
Cited alongside, same era.
D. Scherer, A. Müller, and S. Behnke · 2010
Later among the works it cites.
Improved local coordinate coding using local tangents
K. Yu and T. Zhang · 2010
Later among the works it cites.