Nowadays, deep learning methods are employed in a broad range of research fields. The
analysis and recognition of historical documents, as we survey in this work, is not an …

In this paper, we present an unsupervised feature learning method for page segmentation of
historical handwritten documents available as color images. We consider page …

This paper presents a page segmentation method for handwritten historical document
images based on a Convolutional Neural Network (CNN). We consider page segmentation …

Nowadays, there is a huge amount of Historical Arabic Documents (HAD) in the national
libraries and archives around the world. Analyzing this type of data manually is a difficult and …

Abstract Document Layout Analysis, which is the task of identifying different semantic
regions inside of a document page, is a subject of great interest for both computer scientists …

As a shining pearl in traditional Tibetan culture, historical Tibetan documents have received
extensive attention from historians, linguists and Buddhist scholars. These documents are …

This thesis, first defines the goal of Keyword Spotting from a Decision Theory perspective.
Then, the problem is tackled following a probabilistic formulation. More precisely, Keyword …

In this paper, we study the problem of discovering a timeline of events in a temporal network.
We model events as dense subgraphs that occur within intervals of network activity. We …

Page segmentation is a fundamental and challenging task in document image analysis due
to the layout diversity. In this work, we propose a pixel-wise segmentation method for …

With the passing of history, precious cultural heritage was left behind to tell ancient stories,
especially those in the form of written documents. In this paper, a weakly supervised …