On-line cursive script recognition using time-delay neural networks and hidden Markov models

Schenkel, M.; Guyon, Isabelle; Henderson, D.

doi:10.1007/bf01219589

Cited by 78 publications

(31 citation statements)

References 15 publications

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“…Among many, more specifically, template based approaches have a long standing record [4,11,19,36,41]. In many of the cases, writer independent recogniser has been made since every new user does not require training -which is widely acceptable.…”

Section: Why Writer Independent?mentioning

confidence: 99%

Stroke-Based Cursive Character Recognition

Santosh¹,

Iwata²

2012

Advances in Character Recognition

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Section: Why Writer Independent?mentioning

confidence: 99%

Stroke-Based Cursive Character Recognition

Santosh¹,

Iwata²

2012

Advances in Character Recognition

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“…This system, usually referred to as the hybrid HMM/ANN combines HMM sequential modeling structure with ANN pattern classification (Bourlard & Morgan, 1993). Although this approach is quite general and recently was also used for handwriting recognition (Schenkel, Guyon, et al, 1994;Schenkel, Guyon, et al, 1995) and speaker verification , the following description will mainly apply to ASR problems.…”

Section: Hybrid Hmm/ann Approachmentioning

confidence: 99%

Survey of the State of the Art in Human Language Technology

Cohen¹,

Varile²,

Zampolli³

et al. 2000

Language

133

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“…This technique of replacing the likelihood by the posterior estimated from a discriminative classifier has shown to improve the discrimination capability of generative models [9,22].…”

Section: Refinement Of Component Detection Based On Classificationmentioning

confidence: 99%

Automatic 3D face reconstruction from single images or video

Breuer

Kim²,

Kienzle³

et al. 2008

2008 8th IEEE International Conference on Automatic Face &Amp; Gesture Recognition

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This paper presents a fully automated algorithm for reconstructing a textured 3D model of a face from a single photograph or a raw video stream. The algorithm is based on a combination of Support Vector Machines (SVMs) and a Morphable Model of 3D faces. After SVM face detection, individual facial features are detected using a novel regression-and classification-based approach, and probabilistically plausible configurations of features are selected to produce a list of candidates for several facial feature positions. In the next step, the configurations of feature points are evaluated using a novel criterion that is based on a Morphable Model and a combination of linear projections. To make the algorithm robust with respect to head orientation, this process is iterated while the estimate of pose is refined. Finally, the feature points initialize a model-fitting procedure of the Morphable Model. The result is a highresolution 3D surface model.

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On-line cursive script recognition using time-delay neural networks and hidden Markov models

Cited by 78 publications

References 15 publications

Stroke-Based Cursive Character Recognition

Stroke-Based Cursive Character Recognition

Survey of the State of the Art in Human Language Technology

Automatic 3D face reconstruction from single images or video

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