Convolutional Neural Networks (CNNs) are deep learning models that are trained to
automatically extract the most discriminating features directly from an input image to be used …

We propose a pyramid-based method for keyword spotting in historical document images.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 …

The current paper gives an overview on the technologies used in word spotting especially
for handwritten documents. We present recent interesting published researches in this …

Retrieving information from a huge collection of ancient handwritten documents is important
for indexing, interpreting, browsing, and searching documents in various domains. Word …

The researchers have focused on the techniques used to create systems for data protection
such as signature verification, investigation in crimes, handwriting mails, graphical …

This paper presents an object recognition module development. This module uses a local
feature approach to identify keypoints in free form objects and an unsupervised artificial …

Natural images are easier to represent in feature space than textual images due to the
reduced complexity and thus do not require greater learning capacity. The visual information …

Vast number of historical Arabic manuscripts is available in digital form on-line where
automatic classification, indexing, and retrieval maybe needed. Such tasks depend heavily …

Feature extraction is a crucial stage of pattern recognition systems. The advances in
computer vision and machine learning have developed generic frameworks that could …

Im Gegensatz zur Texterkennung in maschinengeschriebenen Dokumenten, die
weitgehend als gelöstes Problem der Informatik gesehen werden kann, ist die …