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 …

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 …

Imagine a world where people constantly try to pass through walls and cars suddenly leave
the roads and drive into rivers. Although this is unrealistic, most simulations for mobile ad …

In this paper we present an efficient segmentation-free word spotting method, applied in the
context of historical document collections, that follows the query-by-example paradigm. We …

There are two types of information in each handwritten word image: explicit information
which can be easily read or derived directly, such as lexical content or word length, and …

We present a framework for learning an efficient holistic representation for handwritten word
images. The proposed method uses a deep convolutional neural network with traditional …

We present a review of recent techniques for performing geometric analysis in cultural
heritage (CH) applications. The survey is aimed at researchers in the areas of computer …

We address the problem of predicting similarity between a pair of handwritten document
images written by potentially different individuals. This has applications related to matching …

Prior knowledge plays an important role in increasing the performance of support vector
machine (SVM). One way to utilize prior knowledge is to assign different weight to each …

In this paper, we approach the problem of segmentation-free query-by-string word spotting
for handwritten documents. In other words, we use methods inspired from computer vision …