Optical character recognition (OCR) is one of the most popular techniques used for
converting printed documents into machine-readable ones. While OCR engines can do well …

This paper addresses human pose recognition from video sequences by formulating it as a
classification problem. Unlike much previous work we do not make any assumptions on the …

This paper presents a novel method for improving optical character recognition (OCR). The
method employs the progressive alignment of hypotheses from multiple OCR engines …

Abstract The adoption of Optical Character Recognition (OCR) tools has been central to the
increased digitization of historical documents. However, the errors introduced during OCR …

As the digitization of historical documents, such as newspapers, becomes more common,
the need of the archive patron for accurate digital text from those documents increases …

How can scholarly editors best make use of recent developments in Handwritten Text
Recognition (HTR), where the products of automated text recognition can appear as …

Our previous work has shown that the error correction of optical character recognition (OCR)
on degraded historical machine-printed documents is improved with the use of multiple …

The approach of OCR multiple outputs is used to improve accuracy for low scanning
resolution images. The idea of this approach is to incorporate information from multiple …

Optical character recognition (OCR) is the electronic transformation of images into a
computer-encoded text. OCR systems often produce poor accuracy for noisy images …

The usefulness of digitized documents is directly related to the quality of the extracted text.
Optical Character Recognition (OCR) has reached a point where well-formatted and clean …