With the development of deep learning in satellite remote sensing image segmentation, convolutional neural networks have achieved better results than traditional methods. In some full networks, number network layers usually increases to obtain features, but gradient disappearance problem occurs when deepens. Many scholars obtained multiscale features by using different calculations. We want str...

Dimensionality reduction has been shown to improve processing and information extraction from high dimensional data. Word space algorithms typically employ linear reduction techniques that assume the space is Euclidean. We investigate the effects of extracting nonlinear structure in the word space using Locality Preserving Projections, a reduction algorithm that performs manifold learning. We a...

The authors present an ontology-based information extraction process, which operates in a bootstrapping framework. The novelty of this approach lies in the continuous semantics extraction from textual content in order to evolve the underlying ontology, while the evolved ontology enhances in turn the information extraction mechanism. This process was implemented in the context of the R&D project...

In this paper, we present a database and methods for off-line isolated Greek handwritten character recognition. The Computational Intelligence Laboratory (CIL) Database consists of 35,000 isolated and labelled Greek handwritten characters. This database was tested with an existing structural approach for Greek handwritten characters as well as with a novel approach based on a hybrid feature ext...

Based on CART, we introduce a recursive partitioning method for high dimensional space which partitions the data using low dimensional features. The low dimensional features are extracted via an exploratory projection pursuit (EPP) method, localized to each node in the tree. In addition, we present an exploratory splitting rule that is potentially less biased to the training data. This leads to...

In this paper we propose a dimension reduction method to estimate the directions in a multiple-index regression based on information extraction. This extends the recent work of Yin and Cook (2005) who introduced the method and used it to estimate the direction in a single-index regression. While a formal extension seems conceptually straightforward, there is a fundamentally new aspect of our ex...

Visual Information Extraction (VIE) is a technique that enables users to perform information extraction from visual documents driven by the visual appearance and the spatial relations occurring among the elements in the document. In particular, the extractions are expressed through a query language similar to the well known SQL. To further reduce the human effort in the extraction task, in this...

Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a ...