Vast collections of documents available in image format need to be indexed for information
retrieval purposes. In this framework, word spotting is an alternative solution to optical …

Natural history collections (NHCs) are the foundation of historical baselines for assessing
anthropogenic impacts on biodiversity. Along these lines, the online mobilization of …

It is estimated that in 2015, approximately 1.8 million people infected by tuberculosis died,
most of them in developing countries. Many of those deaths could have been prevented if …

The success of deep learning based models have centered around recent architectures and
the availability of large scale annotated data. In this work, we explore these two factors …

Optical character recognition (OCR) systems performance have improved significantly in the
deep learning era. This is especially true for handwritten text recognition (HTR), where each …

Purpose An overview of the current use of handwritten text recognition (HTR) on archival
manuscript material, as provided by the EU H2020 funded Transkribus platform. It explains …

Human activity recognition (HAR) is a classification task for recognizing human movements.
Methods of HAR are of great interest as they have become tools for measuring occurrences …

Providing computers with the ability to process handwriting is both important and
challenging, since many difficulties (eg, different writing styles, alphabets, languages, etc.) …

This work presents a two-stage text line detection method for historical documents. Each
detected text line is represented by its baseline. In a first stage, a deep neural network called …

Global pooling layers are an essential part of Convolutional Neural Networks (CNN). They
are used to aggregate activations of spatial locations to produce a fixed-size vector in …