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This paper presents a page segmentation method for handwritten historical document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 …

This paper introduces a publicly available historical manuscript database DIVA-HisDB for
the evaluation of several Document Image Analysis (DIA) tasks. The database consists of …

We present 1) a work in progress method to visually segment key regions of scientific
articles using an object detection technique augmented with contextual features, and 2) a …

In this paper, we present a novel approach for initializing deep neural networks, ie, by using
Principal Component Analysis (PCA) to initialize neural layers. Usually, the initialization of …

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 …

In this paper, we present an efficient page segmentation method for historical document
images. Many existing methods either rely on hand-crafted features or perform rather slow …

Over the years, the humanities community has increasingly requested the creation of
artificial intelligence frameworks to help the study of cultural heritage. Document Layout …

In this paper, we present a Conditional Random Field (CRF) model to deal with the problem
of segmenting handwritten historical document images into different regions. We consider …

Modeling and analysis of program behavior are at the foundation of computer system design
and optimization. As computer systems become more adaptive, their efficiency increasingly …