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Recognition Tasks are Imitation Games
"... There is need for more formal specification of recognition tasks. Currently, it is common to use labeled training samples to illustrate the task to be performed. The mathematical theory of games may provide more formal and complete definitions for recognition tasks. We present
..."
Abstract
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Cited by 1 (1 self)
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There is need for more formal specification of recognition tasks. Currently, it is common to use labeled training samples to illustrate the task to be performed. The mathematical theory of games may provide more formal and complete definitions for recognition tasks. We present
Gradient-based learning applied to document recognition
- Proceedings of the IEEE
, 1998
"... Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradientbased learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify hi ..."
Abstract
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Cited by 1533 (84 self)
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high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten character recognition and compares them on a standard handwritten digit recognition task. Convolutional neural networks, which are specifically designed
Maximum Likelihood Linear Transformations for HMM-Based Speech Recognition
- COMPUTER SPEECH AND LANGUAGE
, 1998
"... This paper examines the application of linear transformations for speaker and environmental adaptation in an HMM-based speech recognition system. In particular, transformations that are trained in a maximum likelihood sense on adaptation data are investigated. Other than in the form of a simple bias ..."
Abstract
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Cited by 570 (68 self)
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-space transforms on a large vocabulary speech recognition task using incremental adaptation is investigated. In addition, initial experiments using the constrained model-space transform for speaker adaptive training are detailed.
Exploiting Human Actions and Object Context for Recognition Tasks
, 1999
"... Our goal is to exploit human motion and object context to perform action recognition and object classification. Towards this end, we introduce a framework for recognizing actions and objects by measuring image-, object- and action-based information from video. Hidden Markov models are combined with ..."
Abstract
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Cited by 158 (6 self)
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Our goal is to exploit human motion and object context to perform action recognition and object classification. Towards this end, we introduce a framework for recognizing actions and objects by measuring image-, object- and action-based information from video. Hidden Markov models are combined
Hierarchical Models of Object Recognition in Cortex
, 1999
"... The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore th ..."
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Cited by 836 (84 self)
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the biological feasibility of this class of models to explain higher level visual processing, such as object recognition. We describe a new hierarchical model that accounts well for this complex visual task, is consistent with several recent physiological experiments in inferotemporal cortex and makes testable
Comparison of classifier fusion methods for classification in pattern recognition tasks
- Lecture Notes in Computer Science
"... pattern recognition tasks ..."
Recognition tasks are imitation games
- In LNCS, volume 3686
, 2005
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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Cited by 1 (1 self)
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All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Speech recognition tasks
, 2011
"... This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or sel ..."
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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit:
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