Image segmentation, the partitioning of an image into meaningful parts, is a major concern of any computer vision system. The meaningful parts of a text image are lines of text, words and characters. In this paper, the segmentation of pages of text into lines of text and lines of text into characters on a parallel machine will be examined. Using a parallel machine for text image segmentation al...

We propose a novel model for music structural segmentation aiming at combining harmonic and timbral information. We use two-level clustering with splitting initialization and random turbulence to produce segment labels using chroma and MFCC separately as feature. We construct a score matrix to combine segment labels from both aspects. Finally Nonnegative Matrix Factorization and Maximum Likelih...

This report describes analogic algorithms used in the preprocessing and segmentation phase of off-line handwriting recognition tasks. A segmentation based handwriting recognition approach is discussed i.e. the system attempts to segment the words into their constituent letters. In order to improve their speed, the utilized CNN algorithms, whenever possible, use dynamic, wave front propagationba...

We investigate the novel problem of event recognition from news webpages. “Events” are basic text units containing news elements. We observe that a news article is always constituted by more than one event, namely Latent Ingredients (LIs) which form the whole document. Event recognition aims to mine these Latent Ingredients out. Researchers have tackled related problems before, such as discours...

Topic segmentation plays an important role for discourse analysis and document understanding. Previous work mainly focus on unsupervised method for topic segmentation. In this paper, we propose to use bidirectional long shortterm memory(BLSTM) model, along with convolutional neural network(CNN) for learning paragraph representation. Besides, we present a novel algorithm based on frequent subseq...

In this work, control strategies for combining two potentially powerful buuer management techniques in object bases were devised and evaluated: (1) buuer pool segmentation with segment-speciic replacement criteria, and (2) dual buuering consisting of copying objects from pages into object buuers. Two dimensions exist for exerting control on the buuer pool: (1) the copying time which determines ...

Topic Segmentation is the task of breaking documents into topically coherent multi-paragraph subparts. In particular, Topic Segmentation is extensively used in Passage Retrieval and Text Summarization to provide more coherent results by taking into account raw document structure. However, most methodologies are based on lexical repetition that show evident reliability problems or rely on harves...

Magnetic resonance imaging and spectroscopy (MRI/MRS) plays a unique role in multiple sclerosis (MS) evaluation, because of its ability to provide both high image contrast and significant chemical change among brain tissues. The image contrast renders the possibility of quantifying the tissue volumetric and texture variations, e.g., cerebral atrophy and progressing speed, reflecting the ongoing...

Automatic Web comment detection could significantly facilitate information retrieval systems, e.g., a focused Web crawler. In this paper, we propose a text genre classifier for Web text segments as intermediate step for Web comment detection in Web pages. Different feature types and classifiers are analyzed for this purpose. We compare the two-level approach to state-ofthe-art techniques operat...