Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier]
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Derek C. Rose | D C Rose | I Arel | T P Karnowski | I. Arel | T. Karnowski
[1] Kunihiko Fukushima,et al. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.
[3] K. De Jong,et al. Evolving intelligent agents: A 50 year quest , 2008, IEEE Computational Intelligence Magazine.
[4] Yann LeCun,et al. Synergistic Face Detection and Pose Estimation with Energy-Based Models , 2004, J. Mach. Learn. Res..
[5] Dileep George,et al. How the brain might work: a hierarchical and temporal model for learning and recognition , 2008 .
[6] Abdesselam Bouzerdoum,et al. A new class of convolutional neural networks (SICoNNets) and their application of face detection , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..
[7] Jeffrey W. Miller,et al. Biomimetic sensory abstraction using hierarchical quilted self-organizing maps , 2006, SPIE Optics East.
[8] Hossein Mobahi,et al. Deep Learning via Semi-supervised Embedding , 2012, Neural Networks: Tricks of the Trade.
[9] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[10] Geoffrey E. Hinton,et al. Phoneme recognition using time-delay neural networks , 1989, IEEE Trans. Acoust. Speech Signal Process..
[11] E. Rolls,et al. INVARIANT FACE AND OBJECT RECOGNITION IN THE VISUAL SYSTEM , 1997, Progress in Neurobiology.
[12] Honglak Lee,et al. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.
[13] R. Weale. Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr , 1983 .
[14] J. Hawkins,et al. On Intelligence , 2004 .
[15] Sven Behnke,et al. Hierarchical Neural Networks for Image Interpretation (Lecture Notes in Computer Science) , 2003 .
[16] D. Hubel,et al. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.
[17] Patrice Y. Simard,et al. Best practices for convolutional neural networks applied to visual document analysis , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..
[18] T. Poggio,et al. Hierarchical models of object recognition in cortex , 1999, Nature Neuroscience.
[19] Marc'Aurelio Ranzato,et al. Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[20] Geoffrey E. Hinton,et al. Learning Multilevel Distributed Representations for High-Dimensional Sequences , 2007, AISTATS.
[21] Alan J Lockett and Risto Miikkulainen. Temporal Convolution Machines for Sequence Learning , 2009 .
[22] D. Mumford,et al. The role of the primary visual cortex in higher level vision , 1998, Vision Research.
[23] Sean R Eddy,et al. What is dynamic programming? , 2004, Nature Biotechnology.
[24] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[25] Andy Adler,et al. Comparing Human and Automatic Face Recognition Performance , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[26] K. A. De Jong,et al. Evolving intelligent agents: A 50 year quest , 2008, IEEE Comput. Intell. Mag..
[27] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[28] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[29] Kunihiko Fukushima,et al. Neocognitron for handwritten digit recognition , 2003, Neurocomputing.
[30] Yoshua Bengio,et al. An empirical evaluation of deep architectures on problems with many factors of variation , 2007, ICML '07.
[31] Thomas Serre,et al. Robust Object Recognition with Cortex-Like Mechanisms , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[32] Ying-Nong Chen,et al. The Application of a Convolution Neural Network on Face and License Plate Detection , 2006, 18th International Conference on Pattern Recognition (ICPR'06).
[33] Kunihiko Fukushima,et al. Restoring partly occluded patterns: a neural network model , 2005, Neural Networks.
[34] Glenn Carroll,et al. On the Prospects for Building a Working Model of the Visual Cortex , 2007, AAAI.
[35] P. Jonathon Phillips,et al. Meta-Analysis of Third-Party Evaluations of Iris Recognition , 2007, 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems.
[36] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[37] Xin Yao,et al. Evolving artificial neural network ensembles , 2008 .
[38] Bogdan Kwolek,et al. Face Detection Using Convolutional Neural Networks and Gabor Filters , 2005, ICANN.
[39] Geoffrey E. Hinton,et al. A time-delay neural network architecture for isolated word recognition , 1990, Neural Networks.
[40] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[41] Somsak Sukittanon,et al. Convolutional networks for speech detection , 2004, INTERSPEECH.
[42] H. Bülthoff,et al. Learning to recognize objects , 1999, Trends in Cognitive Sciences.
[43] Tai Sing Lee,et al. Hierarchical Bayesian inference in the visual cortex. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.
[44] Thomas Hofmann,et al. Greedy Layer-Wise Training of Deep Networks , 2007 .
[45] Itamar Arel,et al. DeSTIN: A Scalable Deep Learning Architecture with Application to High-Dimensional Robust Pattern Recognition , 2009, AAAI Fall Symposium: Biologically Inspired Cognitive Architectures.
[46] Yann LeCun,et al. Large-scale Learning with SVM and Convolutional for Generic Object Categorization , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[47] Yoshua. Bengio,et al. Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..
[48] Hossein Mobahi,et al. Deep learning from temporal coherence in video , 2009, ICML '09.
[49] B. Ripley,et al. Pattern Recognition , 1968, Nature.
[50] Sven Behnke,et al. Hierarchical Neural Networks for Image Interpretation , 2003, Lecture Notes in Computer Science.
[51] Thomas Dean,et al. A Computational Model of the Cerebral Cortex , 2005, AAAI.
[52] Stephen V. Rice,et al. The Fourth Annual Test of OCR Accuracy , 1995 .
[53] 緒方 淳,et al. Real-time pedestrian detection using LIDAR and convolutional neural networks (特集 安全技術) , 2007 .
[54] Yann LeCun,et al. Deep belief net learning in a long-range vision system for autonomous off-road driving , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[55] Honglak Lee,et al. Unsupervised feature learning for audio classification using convolutional deep belief networks , 2009, NIPS.
[56] R. Fergus,et al. Learning invariant features through topographic filter maps , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.