Publication

Datasets and Models for Historical Newspaper Article Segmentation

Maud Ehrmann, Sofia Ares Oliveira, Raphaël Barman
2021
Datasets

Abstract

Dataset and models used and produced in the work described in the paper "Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers": https://infoscience.epfl.ch/record/282863?ln=en

Official source

https://infoscience.epfl.ch/entities/publication/d37f7a96-0e07-490d-a367-2137bd4f9477

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Maud Ehrmann, Sofia Ares Oliveira, Raphaël Barman
2021
Datasets

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/d37f7a96-0e07-490d-a367-2137bd4f9477

About this result

Related concepts (6)

Natural language processing

Natural language processing (NLP) is an interdisciplinary subfield of linguistics and computer science. It is primarily concerned with processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic (i.e. statistical and, most recently, neural network-based) machine learning approaches. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them.

Image segmentation

In and computer vision, image segmentation is the process of partitioning a into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.

Text segmentation

Text segmentation is the process of dividing written text into meaningful units, such as words, sentences, or topics. The term applies both to mental processes used by humans when reading text, and to artificial processes implemented in computers, which are the subject of natural language processing. The problem is non-trivial, because while some written languages have explicit word boundary markers, such as the word spaces of written English and the distinctive initial, medial and final letter shapes of Arabic, such signals are sometimes ambiguous and not present in all written languages.

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