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Handwritten Digit Classification using Higher Order Singular Value Decomposition
"... In this paper we present two algorithms for handwritten digit classification based on the higher order singular value decomposition (HOSVD). The first algorithm uses HOSVD for construction of the class models and achieves classification results with error rate lower than 6%. The second algorithm use ..."
Abstract

Cited by 15 (1 self)
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In this paper we present two algorithms for handwritten digit classification based on the higher order singular value decomposition (HOSVD). The first algorithm uses HOSVD for construction of the class models and achieves classification results with error rate lower than 6%. The second algorithm uses the HOSVD for tensor approximation simultaneously in two modes. Classification results for the second algorithm are almost down at 5 % even though the approximation reduces the original training data with more than 98 % before the construction of the class models. The actual classification in the test phase for both algorithms is conducted by solving a series least squares problems. Considering computational amount for the test presented the second algorithm is twice as efficient as the first one.
Adaptive Online Recognition of Handwriting
, 1998
"... Contents 1 Background 4 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2 Types of handwriting recognition systems . . . . . . . . . . . . . . . . 5 1.2.1 Ooeline recognition . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.2 Online recognition . . . . . ..."
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Cited by 9 (6 self)
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Contents 1 Background 4 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2 Types of handwriting recognition systems . . . . . . . . . . . . . . . . 5 1.2.1 Ooeline recognition . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.2 Online recognition . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.3 Character sets . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.4 Writing style variations . . . . . . . . . . . . . . . . . . . . . . 7 1.2.4.1 Variations of characters . . . . . . . . . . . . . . . . 7 1.2.4.2 Alignment of characters . . . . . . . . . . . . . . . . 8 1.2.4.3 Personal background factors . . . . . . . . . . . . . . 8 1.2.4.4 Situational factors . . . . . . . . . . . . . . . . . . . 9 1.2.4.5 Material factors . . . . . . . . . . . . . . . . . . . . . 9 1.2.4.6 Constraints on writing . . . . . . . . . . . . . . . . . 9 1.2.5 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.3 Beneøt
TAUSKY D.: A preliminary report on the mathbrush penmath system
 In Maple Conference 2006 Proceedings
, 2006
"... In this paper we give a preliminary description of an experimental system, currently named MathBrush, for working with mathematics using penbased devices. The system allows a user to enter mathematical expressions with a pen and to then do mathematical computation using a computer algebra system. T ..."
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Cited by 6 (1 self)
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In this paper we give a preliminary description of an experimental system, currently named MathBrush, for working with mathematics using penbased devices. The system allows a user to enter mathematical expressions with a pen and to then do mathematical computation using a computer algebra system. The system provides a simple and easy way for users to verify the correctness of their handwritten expressions and, if needed, to correct any errors in recognition. Choosing mathematical operations is done making use of context menus, both with input and output expressions. Key words: PCtablets, Penbased input, Maple 1
MathBrush: An Experimental PenBased Math System
"... It is widely believed that mathematics will be one of the major applications for Tablet PCs and other penbased devices. In this paper we discuss many of the issues that make doing mathematics on such penbased devices a hard task. We give a preliminary description of an experimental system, current ..."
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Cited by 4 (0 self)
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It is widely believed that mathematics will be one of the major applications for Tablet PCs and other penbased devices. In this paper we discuss many of the issues that make doing mathematics on such penbased devices a hard task. We give a preliminary description of an experimental system, currently named MathBrush, for working with mathematics using penbased devices. The system allows a user to enter mathematical expressions with a pen and to then do mathematical computation using a computer algebra system. The system provides a simple and easy way for users to verify the correctness of their handwritten expressions and, if needed, to correct any errors in recognition. Choosing mathematical operations is done making use of context menus, both with input and output expressions. Key words: PCtablets, Penbased math, Computer Algebra systems 1
Sketch Understanding for Engineering Software
, 2003
"... this document.) Data points are collected as a time sequenced (x,y) points sampled along the stylus' trajectory. The program gathers these points and attempts to fit one of the two types of geometric primitives: (1) A straight line segment, or (2) An arc segment of a circle. We refer to this proces ..."
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this document.) Data points are collected as a time sequenced (x,y) points sampled along the stylus' trajectory. The program gathers these points and attempts to fit one of the two types of geometric primitives: (1) A straight line segment, or (2) An arc segment of a circle. We refer to this process as `segmentation '. Figure 5 shows an example. The figure on the left corresponds to the unprocessed ink as obtained directly from the digitizing tablet. The figure on the right shows the resulting symbol after segmentation
Examination committee:
"... Handwriting is one of the most natural ways for a human to record knowledge. In recent years this type of humancomputer interaction has received increasing attention due to the rapid evolution of digital ink hardware. This thesis contributes to the art of efficient recognition of handwriting and co ..."
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Handwriting is one of the most natural ways for a human to record knowledge. In recent years this type of humancomputer interaction has received increasing attention due to the rapid evolution of digital ink hardware. This thesis contributes to the art of efficient recognition of handwriting and compact storage of digital ink. In the first part of the thesis, we focus on the development of algorithms for transformationinvariant recognition of handwritten mathematical characters. We first implement a rotationindependent classification method based on the theory of integral invariants of parametric curves. We then extend this method to shearinvariant recognition. Presence of affine transformations creates difficulties in parameterization of coordinate functions and size normalization of handwritten samples. We therefore present an affineinvariant size normalization approach and develop a mixed parameterization, which is insensitive to large affine transformations and yields a relatively high recognition rate.