Titlebook: Document Analysis and Recognition - ICDAR 2024; 18th International C Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng Conference proceedi

Modicum

Ornithologist

obsession

Catheter

J?rn Ahrens,Michael Cuntz,Philipp Schulte0 to 1940, which are preserved in over 130,000 scans of double pages. Each marriage record may encompass up to 118 distinct types of information that require extraction from plain text. In this paper, we introduce the M-POPP dataset, a subset of the M-POPP database with annotations for full-page tex

LIMIT

nalysis, such as studying handwriting styles and typefaces or realigning fragments based on a continuation of text lines. This paper tests and compares various architectures, originally designed for object detection tasks, for text line segmentation in ancient Egyptian hieratic papyri. The corpus us

geometrician

omography enables 3D digital replicas, direct examination is inconvenient. To facilitate content analysis, various virtual unfolding methods have been proposed. We present a groundbreaking, fully automated system for virtual unfolding/unrolling, employing a neural network to generate a binary docume

反復(fù)無常

TSH582

textual information in large collections?of untranscribed text images. The spots that result from the?PrIx process are not image transcripts, but they provide very?rich probabilistic information about the text rendered in specific regions or locations of the images. This paper presents approaches th

Graves’-disease

classification, and document editing. Although several synthetic datasets have been developed to distinguish handwriting from printed text, they fall short in class variety and document diversity. We demonstrate the limitations of training on existing datasets when solving the National Archives Form

corn732