Along with the explosive growth of the amount of handwritten documents that are preserved,
processed and accessed in a digital form, handwritten document images word spotting has …

In this paper we present a novel descriptor and method for segmentation-based keyword
spotting. We introduce Zoning-Aggregated Hypercolumn features as pixel-level cues for …

Following recent advances on parameterized hypercomplex multiplication, we explore the
usefulness of hypercomplex convolutions and deconvolutions in a document labeling task …

The established paradigm in handwriting recognition techniques involves supervised
learning, where training is performed over fully labelled (transcribed) data. In this paper, we …

Quaternionized versions of standard (real-valued) neural network layers have shown to lead
to networks that are sparse and as effective as their real-valued counterparts. In this work …

Abstract Modern Keyword Spotting systems rely on deep learning approaches to build
effective neural networks which provide state-of-the-art results. Despite their evident …

The presented thesis follows two directions. The first one disposes a technique for text and
graphic separation in comics. The second one points out a learning free segmentation free …

Treating visual object tracking as foreground and background classification problem has
attracted much attention in the past decade. Most methods adopt mean shift or brute force …

We propose a pyramid-based method for keyword spotting in historical document images.
The documents are represented by a scale-space pyramid of their features. The search for a …

A wealth of knowledge is kept in libraries and cultural institutions in various digital forms
without, however, the possibility of a simple term search, let alone of a substantial semantic …