Fetching the paper…
Reading the bibliography…
Convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis.
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever and R. Salakhutdinov, Dropout: A simple way to prevent neural networks from overfitting , Journal of Machine Learning Research 15
1958
Earlier work this paper cites.
Spartan Books, 1961
F. Rosenblatt, Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms · 1961
Earlier work this paper cites.
D. Hubel and T. Wiesel, Receptive fields and functional architecture of monkey striate cortex , Journal of Physiology 195
1968
Earlier work this paper cites.
MIT Press, 1986
D. E. Rumelhart, J. L. McClelland and C. PDP Research Group, eds., Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol. 1: Foundations · 1986
Earlier work this paper cites.
D. E. Rumelhart, G. E. Hinton and R. J. Williams, Learning representations by back-propagating errors , Nature 323
1986
Earlier work this paper cites.
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard et al., Backpropagation applied to handwritten zip code recognition , Neural Comput. 1
1989
Earlier work this paper cites.
K. Hornik, M. Stinchcombe and H. White, Multilayer feedforward networks are universal approximators , Neural Networks 2
1989
Earlier work this paper cites.
G. Cybenko, Approximation by superposition of a sigmoidal function , Math. Control Signals System 2
1989
Earlier work this paper cites.
N. S. Altman, An introduction to kernel and nearest-neighbor nonparametric regression , The American Statistician 46
1992
Earlier work this paper cites.
A. Bettini et al., The ICARUS liquid argon TPC: A Complete imaging device for particle physics , Nucl. Instrum. Meth. A315
1992
Earlier work this paper cites.
Sage Publ., 1997
J. Long, Regression models for categorical and limited dependent variables · 1997
Earlier work this paper cites.
Springer Berlin Heidelberg, 1998
Y. LeCun, L. Bottou, G. B. Orr and K. R. Müller, Neural Networks: Tricks of the Trade · 1998
Earlier work this paper cites.
K. Anderson et al., The NuMI Facility Technical Design Report , FERMILAB-DESIGN-1998-01
1998
Earlier work this paper cites.
A Bradford book. MIT Press, 1999
R. Reed and R. Marks, Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks · 1999
Cited alongside, same era.
C. Bassin, G. Laske and G. Masters, The current limits of resolution for surface wave tomography in north america , EOS Trans. AGU 81, F897, 2000
2000
Cited alongside, same era.
J. H. Friedman, Stochastic gradient boosting , Computational Statistics & Data Analysis 38
2002
Cited alongside, same era.
S. Fukuda et al., The super-kamiokande detector , Nucl. Instrum. Meth. A 501
2003
Cited alongside, same era.
S. Agostinelli et al., Geant4 - a simulation toolkit , Nucl. Instrum. Meth. A506
2003
Cited alongside, same era.
A. Ferrari, P. R. Sala, A. Fassò and J. Ranft, FLUKA: A multi-particle transport code (program version 2005) , CERN-2005-010, SLAC-R-773, INFN-TC-05-11
A. Krizhevsky, I. Sutskever and G. E. Hinton, Imagenet classification with deep convolutional neural networks , in Advances in Neural Information Processing Systems 25 , pp. 1097–1105, 2012
2012
Later among the works it cites.
C. Farabet, C. Couprie, L. Najman and Y. LeCun, Learning hierarchical features for scene labeling , IEEE Transactions on Pattern Analysis and Machine Intelligence (August, 2013)
2013
Later among the works it cites.
M. Lin, Q. Chen and S. Yan, Network in network , in International Conference on Learning Representations , 2014 · 2014
Later among the works it cites.
T. T. Böhlen, F. Cerutti, M. P. W. Chin, A. Fassò, A. Ferrari, P. G. Ortega et al., The FLUKA code: Developments and challenges for high energy and medical applications , Nuclear Data Sheets 120
2014
Later among the works it cites.
Particle Data Group
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2005
Cited alongside, same era.
Springer-Verlag New York, Inc., 2006
C. M. Bishop, Pattern Recognition and Machine Learning (Information Science and Statistics) · 2006
Cited alongside, same era.
J. Allison et al., Geant4 developments and applications , IEEE Trans. Nucl. Sci. 53
2006
Cited alongside, same era.
J. Nickolls, I. Buck, M. Garland and K. Skadron, Scalable parallel programming with cuda , in Que , 2008
2008
Cited alongside, same era.
Y. Bengio, Learning deep architectures for AI , Foundations and Trends in Machine Learning 2
2009
Cited alongside, same era.
V. Nair and G. E. Hinton, Rectified linear units improve restricted boltzmann machines , in Proceedings of the 27th International Conference on Machine Learning (ICML-10) , pp. 807–814, 2010
2010
Cited alongside, same era.
C. Andreopoulos et al., The GENIE neutrino monte carlo generator , Nucl. Instrum. Meth. A614
2010
Cited alongside, same era.
2014
Later among the works it cites.
Y. LeCun, Y. Bengio and G. Hinton, Deep learning , Nature 521
2015
Later among the works it cites.
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma et al., ImageNet Large Scale Visual Recognition Challenge , International Journal of Computer Vision (IJCV) 115
2015
Later among the works it cites.
A. Aurisano, C. Backhouse, R. Hatcher, N. Mayer, J. Musser, R. Patterson et al., The NOvA simulation chain , J. Phys. Conf. Ser. 664
2015
Later among the works it cites.
M. Baird, J. Bian, M. Messier, E. Niner, D. Rocco and K. Sachdev, Event Reconstruction Techniques in NOvA , J. Phys. Conf. Ser. 664
2015
Later among the works it cites.
J. Long, E. Shelhamer and T. Darrell, Fully convolutional networks for semantic segmentation , in Conference on Computer Vision and Pattern Recognition , 2015 · 2015
Later among the works it cites.
P. Adamson et al., The NuMI Neutrino Beam , Nucl. Instrum. Meth. A806
2016
Closest in time.
P. Adamson et al., First measurement of muon-neutrino disappearance in NOvA , Phys. Rev. D 93
2016
Closest in time.