Fetching the paper…
Reading the bibliography…
Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks.
K. Fukushima, “Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position,” Biological Cybernetics , vol. 36, no. 4, pp. 193–202, 1980
1980
Earlier work this paper cites.
D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature , pp. 533–536, 1986
1986
Earlier work this paper cites.
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel, “Backpropagation applied to handwritten zip code recognition,” Neural computation , vol. 1, no. 4, pp. 541–551, 1989
1989
Earlier work this paper cites.
C. Mead, “Neuromorphic electronic systems,” Proceedings of the IEEE , vol. 78, no. 10, pp. 1629–1636, 1990
1990
Earlier work this paper cites.
J. Garofolo, L. Lamel, W. Fisher, J. Fiscus, D. Pallett, N. Dahlgren, and V. Zue, “TIMIT Acoustic-Phonetic Continuous Speech Corpus LDC93S1,” Philadelphia: Linguistic Data Consortium , 1993
1993
Earlier work this paper cites.
A. Varga and H. J. M. Steeneken, “Assessment for Automatic Speech Recognition II: NOISEX-92: A Database and an Experiment to Study the Effect of Additive Noise on Speech Recognition Systems,” Speech Communications , vol. 12, no. 3, pp. 247–251, Jul. 1993
1993
Earlier work this paper cites.
A. J. Bell and T. J. Sejnowski, “The Òindependent componentsÓ of natural scenes are edge filters,” Vision research , vol. 37, no. 23, pp. 3327–3338, 1997
1997
Earlier work this paper cites.
H.-A. Chang and J. R. Glass, “Hierarchical large-margin gaussian mixture models for phonetic classification,” in IEEE Workshop on Automatic Speech Recognition and Understanding , 2007
2007
Earlier work this paper cites.
A. Krizhevsky, “Learning multiple layers of features from tiny images,” University of Toronto, Tech. Rep., 2009
2009
Earlier work this paper cites.
T. V. Pham, C. T. Tang, and M. Stadtschnitzer, “Using artificial neural network for robust voice activity detection under adverse conditions,” in International Conference on Computing and Communication Technologies . IEEE, 2009, pp. 1–8
2009
Earlier work this paper cites.
Y. Netzer, T. Wang, A. Coates, A. Bissacco, B. Wu, and A. Y. Ng, “Reading digits in natural images with unsupervised feature learning,” in NIPS Workshop on Deep Learning and Unsupervised Feature Learning 2011 , 2011. [Online]. Available: http://ufldl.stanford.edu/housenumbers/nips2011_housenumbers.pdf
2011
Earlier work this paper cites.
S. Romberg, L. G. Pueyo, R. Lienhart, and R. V. Zwol, “Scalable logo recognition in real-world images,” in Proceedings of the 1st ACM International Conference on Multimedia Retrieval . ACM, 2011, p. 25
2011
Earlier work this paper cites.
P. Merolla, J. Arthur, F. Akopyan, N. Imam, R. Manohar, and D. S. Modha, “A digital neurosynaptic core using embedded crossbar memory with 45pJ per spike in 45nm,” in IEEE Custom Integrated Circuits Conference (CICC) , Sept. 2011, pp. 1–4
2011
Earlier work this paper cites.
D. Cireşan, A. Giusti, L. M. Gambardella, and J. Schmidhuber, “Deep neural networks segment neuronal membranes in electron microscopy images,” in Advances in neural information processing systems , 2012, pp. 2843–2851
2012
Earlier work this paper cites.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in Neural Information Processing Systems , 2012, pp. 1097–1105
2012
Earlier work this paper cites.
R. Preissl, T. M. Wong, P. Datta, M. Flickner, R. Singh, S. K. Esser, W. P. Risk, H. D. Simon, and D. S. Modha, “Compass: A scalable simulator for an architecture for cognitive computing,” in Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis . IEEE Computer Society Press, 2012, p. 54
2012
Cited alongside, same era.
J. Stallkamp, M. Schlipsing, J. Salmen, and C. Igel, “Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition,” Neural networks , vol. 32, pp. 323–332, 2012
2012
Cited alongside, same era.
D. Cireşan, U. Meier, J. Masci, and J. Schmidhuber, “Multi-column deep neural network for traffic sign classification.” Neural networks , vol. 32, pp. 333–338, Aug. 2012
2012
Cited alongside, same era.
A. Amir, P. Datta, W. P. Risk, A. S. Cassidy, J. A. Kusnitz, S. K. Esser, A. Andreopoulos, T. M. Wong, M. Flickner, R. Alvarez-Icaza et al. , “Cognitive computing programming paradigm: a corelet language for composing networks of neurosynaptic cores,” in Neural Networks (IJCNN), The 2013 International Joint Conference on . IEEE, 2013, pp. 1–10
2014
Later among the works it cites.
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolutions,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2015, pp. 1–9
2015
Later among the works it cites.
S. Ren, K. He, R. Girshick, and J. Sun, “Faster r-cnn: Towards real-time object detection with region proposal networks,” in Advances in Neural Information Processing Systems , 2015, pp. 91–99
2015
Later among the works it cites.
E. Stromatias, D. Neil, M. Pfeiffer, F. Galluppi, S. B. Furber, and S.-C. Liu, “Robustness of spiking deep belief networks to noise and reduced bit precision of neuro-inspired hardware platforms,” Frontiers in neuroscience , vol. 9, 2015
2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2013
Cited alongside, same era.
E. Painkras, L. Plana, J. Garside, S. Temple, F. Galluppi, C. Patterson, D. R. Lester, A. D. Brown, S. B. Furber et al. , “Spinnaker: A 1-w 18-core system-on-chip for massively-parallel neural network simulation,” Solid-State Circuits, IEEE Journal of , vol. 48, no. 8, pp. 1943–1953, 2013
2013
Cited alongside, same era.
T. Pfeil, A. Grübl, S. Jeltsch, E. Müller, P. Müller, M. A. Petrovici, M. Schmuker, D. Brüderle, J. Schemmel, and K. Meier, “Six networks on a universal neuromorphic computing substrate,” Frontiers in Neuroscience , vol. 7, 2013
2013
Cited alongside, same era.
A. S. Cassidy, P. Merolla, J. V. Arthur, S. K. Esser, B. Jackson, R. Alvarez-Icaza, P. Datta, J. Sawada, T. M. Wong, V. Feldman et al. , “Cognitive computing building block: A versatile and efficient digital neuron model for neurosynaptic cores,” in Neural Networks (IJCNN), The 2013 International Joint Conference on . IEEE, 2013, pp. 1–10
2013
Cited alongside, same era.
A. Graves, N. Jaitly, and A. Mohamed, “Hybrid speech recognition with deep bidirectional lstm,” in IEEE Workshop on Automatic Speech Recognition and Understanding , 2013, pp. 273–278
2013
Cited alongside, same era.
S. K. Esser, A. Andreopoulos, R. Appuswamy, P. Datta, D. Barch, A. Amir, J. Arthur, A. Cassidy, M. Flickner, P. Merolla et al. , “Cognitive computing systems: Algorithms and applications for networks of neurosynaptic cores,” in Neural Networks (IJCNN), The 2013 International Joint Conference on . IEEE, 2013, pp. 1–10
2013
Cited alongside, same era.
P. A. Merolla, J. V. Arthur, R. Alvarez-Icaza, A. S. Cassidy, J. Sawada, F. Akopyan, B. L. Jackson, N. Imam, C. Guo, Y. Nakamura et al. , “A million spiking-neuron integrated circuit with a scalable communication network and interface,” Science , vol. 345, no. 6197, pp. 668–673, 2014
2014
Cited alongside, same era.
2014
Cited alongside, same era.
2014
Cited alongside, same era.
M. Courbariaux, Y. Bengio, and J.-P. David, “Binaryconnect: Training deep neural networks with binary weights during propagations,” in Advances in Neural Information Processing Systems , 2015, pp. 3105–3113
2015
Later among the works it cites.
2015
Later among the works it cites.
S. Han, J. Pool, J. Tran, and W. Dally, “Learning both weights and connections for efficient neural network,” in Advances in Neural Information Processing Systems , 2015, pp. 1135–1143
2015
Later among the works it cites.
S. K. Esser, R. Appuswamy, P. Merolla, J. V. Arthur, and D. S. Modha, “Backpropagation for energy-efficient neuromorphic computing,” in Advances in Neural Information Processing Systems , 2015, pp. 1117–1125
2015
Later among the works it cites.
A. Vedaldi and K. Lenc, “MatConvNet – convolutional neural networks for MATLAB,” 2015
2015
Later among the works it cites.
2015
Later among the works it cites.
S. Das, B. U. Pedroni, P. Merolla, J. Arthur, A. S. Cassidy, B. L. Jackson, D. Modha, G. Cauwenberghs, and K. Kreutz-Delgado, “Gibbs sampling with low-power spiking digital neurons,” IEEE International Symposium on Circuits and Systems , 2015
2015
Later among the works it cites.
T. M. Bartol, C. Bromer, J. Kinney, M. A. Chirillo, J. N. Bourne, K. M. Harris, and T. J. Sejnowski, “Nanoconnectomic upper bound on the variability of synaptic plasticity,” eLife , vol. 4, p. e10778, 2016
2016
Closest in time.
2016
Closest in time.
2016
Closest in time.