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Results 1 - 10
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13,700
Authorship Attribution and Optical Character Recognition Errors
"... ABSTRACT. Stylometric authorship attribution is a fundamental problem. The basic idea behind the research is that one can determine the authorship of a document on the basis of cognitive and linguistic quirks that uniquely identify a person. In many cases, however, noise in the original documents ca ..."
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can make this analysis more difficult and less reliable. We investigate the errors introduced by a typical optical character recognition (OCR) process. Using simulated (random) errors in a standard benchmark corpus, we test to see how sensitive the authorship attribution process is to character mis-recognition
HANDWRITING CHARACTERS RECOGNITION ERRORS AND RECOGNIZING ERRORS OF CHILDREN ON THE TABLET PC
"... Abstract. In this paper efforts have been made to determine the usability of handwriting recognition technology on a tablet PC for free writing by children. Results demonstrate that recognition error rates vary according to the metrics used, and to discuss how some of the errors are created concludi ..."
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Abstract. In this paper efforts have been made to determine the usability of handwriting recognition technology on a tablet PC for free writing by children. Results demonstrate that recognition error rates vary according to the metrics used, and to discuss how some of the errors are created
Measuring the impact of character recognition errors on downstream text analysis
- In Proceedings of Document Recognition and Retrieval XV (IS&T/SPIE Electronic Imaging
, 2008
"... Noise presents a serious challenge in optical character recognition, as well as in the downstream applications that make use of its outputs as inputs. In this paper, we describe a paradigm for measuring the impact of recognition errors on the stages of a standard text analysis pipeline: sentence bou ..."
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Cited by 1 (1 self)
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Noise presents a serious challenge in optical character recognition, as well as in the downstream applications that make use of its outputs as inputs. In this paper, we describe a paradigm for measuring the impact of recognition errors on the stages of a standard text analysis pipeline: sentence
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 ..."
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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
Robust face recognition via sparse representation
- IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2008
"... We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse signa ..."
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Cited by 936 (40 self)
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. This framework can handle errors due to occlusion and corruption uniformly, by exploiting the fact that these errors are often sparse w.r.t. to the standard (pixel) basis. The theory of sparse representation helps predict how much occlusion the recognition algorithm can handle and how to choose the training
Shape Matching and Object Recognition Using Shape Contexts
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2001
"... We present a novel approach to measuring similarity between shapes and exploit it for object recognition. In our framework, the measurement of similarity is preceded by (1) solv- ing for correspondences between points on the two shapes, (2) using the correspondences to estimate an aligning transform ..."
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Cited by 1809 (21 self)
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for this purpose. The dissimilarity between the two shapes is computed as a sum of matching errors between corresponding points, together with a term measuring the magnitude of the aligning trans- form. We treat recognition in a nearest-neighbor classification framework as the problem of finding the stored
Dynamic programming algorithm optimization for spoken word recognition
- IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING
, 1978
"... This paper reports on an optimum dynamic programming (DP) based time-normalization algorithm for spoken word recognition. First, a general principle of time-normalization is given using timewarping function. Then, two time-normalized distance definitions, ded symmetric and asymmetric forms, are der ..."
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Cited by 788 (3 self)
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to spoken word recognition by different research groups. The experiment shows that the present algorithm gives no more than about twothirds errors, even compared to the best conventional algorithm. categories, a constraint is newly introduced on the warping I.
High confidence visual recognition of persons by a test of statistical independence
- IEEE TRANS. ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1993
"... A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a sample of the ..."
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Cited by 621 (8 self)
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imply a theoretical “cross-over ” error rate of one in 131000 when a decision criterion is adopted that would equalize the false accept and false reject error rates. In the typical recognition case, given the mean observed degree of iris code agreement, the decision confidence levels correspond formally
On-line and Off-line Handwriting Recognition: A Comprehensive Survey
- IEEE Transactions on Pattern Analysis and Machine Intelligence
"... AbstractÐHandwriting has continued to persist as a means of communication and recording information in day-to-day life even with the introduction of new technologies. Given its ubiquity in human transactions, machine recognition of handwriting has practical significance, as in reading handwritten no ..."
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Cited by 495 (8 self)
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-line case (which pertains to the availability of trajectory data during writing) and the off-line case (which pertains to scanned images) are considered. Algorithms for preprocessing, character and word recognition, and performance with practical systems are indicated. Other fields of application, like
From Few to many: Illumination cone models for face recognition under variable lighting and pose
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2001
"... We present a generative appearance-based method for recognizing human faces under variation in lighting and viewpoint. Our method exploits the fact that the set of images of an object in fixed pose, but under all possible illumination conditions, is a convex cone in the space of images. Using a smal ..."
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Cited by 754 (12 self)
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illumination cone (based on Euclidean distance within the image space). We test our face recognition method on 4050 images from the Yale Face Database B; these images contain 405 viewing conditions (9 poses ¢ 45 illumination conditions) for 10 individuals. The method performs almost without error, except
Results 1 - 10
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13,700
