Using vectors

Xem 1-20 trên 350 kết quả Using vectors
  • A three-stage method for compressing bi-level line-drawing images is proposed. In the first stage, the raster image is vectorized using a combination of skeletonizing and line tracing algorithm. A feature image is then reconstructed from the extracted vector elements. In the second stage, the original image is processed by a feature-based filter for removing noise near the borders of the extracted line elements. This improves the image quality and results in more compressible raster image. In the final stage, the filtered raster image is compressed using the baseline JBIG algorithm....

    pdf6p kienk6e 31-03-2011 55 14   Download

  • Yes, today I am going to teach you a very simple way to make a vector portrait (scroll down to see how it looks like). And this really is vector (you can resize it without losing the quality). And to do this, we are going to use Photoshop together with the pretty good and absolutely free, open-source vector program: Inkscape. It works good for portrait, but also on other things.

    doc5p playprang 14-06-2010 78 14   Download

  • Photoshop Elementsis one of the most powerful image editing programs on the planet, bar none. The key to harnessing the power of the program and getting the best results from your images is understanding how the program works, understanding images, and using the inherent capabilities of the program optimally to make the best image adjustments. Getting the most out of your images using Photoshop Elements is what this book is about.

    pdf369p ptng13 25-06-2012 39 9   Download

  • This paper describes methods for relating (threading) multiple newspaper articles, and for visualizing various characteristics of them by using a directed graph. A set of articles is represented by a set of word vectors, and the similarity between the vectors is then calculated. The graph is constructed from the similarity matrix. By applying some constraints on the chronological ordering of articles, an efficient threading algorithm that runs in O(n) time (where n is the number of articles) is obtained. ...

    pdf7p bunrieu_1 18-04-2013 27 3   Download

  • VECTOR DISSIPATIVITY THEORY FOR DISCRETE-TIME LARGE-SCALE NONLINEAR DYNAMICAL SYSTEMS WASSIM M. HADDAD, QING HUI, VIJAYSEKHAR CHELLABOINA, AND SERGEY NERSESOV Received 15 October 2003 In analyzing large-scale systems, it is often desirable to treat the overall system as a collection of interconnected subsystems. Solution properties of the large-scale system are then deduced from the solution properties of the individual subsystems and the nature of the system interconnections.

    pdf30p sting12 10-03-2012 20 3   Download

  • The gene 4CL1 was isolated from Chinese red pine (Pinus massoniana Lamb) and ligated into vector pPTN289 to perform transformation vector pPTN289-4CL1. This construction was transformed into Agrobacterium tumefaciens strain C58, and then transformed into Chinaberrytree (Melia azedarach L.). The transgenic Chinaberrytree was screened on selection medium (MS + 0.5mg/l 6-BA + 1mg/l vitamine B5 + 30g/l sucrose + 8g/l agar + 500mg/l Cefotaxime + 1mg/l PPT) and then extracted total DNA and tested the existence of interested gene using PCR method. ...

    pdf7p tuanlocmuido 13-12-2012 20 2   Download

  • We present a syntactically enriched vector model that supports the computation of contextualized semantic representations in a quasi compositional fashion. It employs a systematic combination of first- and second-order context vectors. We apply our model to two different tasks and show that (i) it substantially outperforms previous work on a paraphrase ranking task, and (ii) achieves promising results on a wordsense similarity task; to our knowledge, it is the first time that an unsupervised method has been applied to this task. ...

    pdf10p hongdo_1 12-04-2013 22 2   Download

  • Unsupervised vector-based approaches to semantics can model rich lexical meanings, but they largely fail to capture sentiment information that is central to many word meanings and important for a wide range of NLP tasks. We present a model that uses a mix of unsupervised and supervised techniques to learn word vectors capturing semantic term–document information as well as rich sentiment content.

    pdf9p hongdo_1 12-04-2013 20 2   Download

  • Graph-based dependency parsing can be sped up significantly if implausible arcs are eliminated from the search-space before parsing begins. State-of-the-art methods for arc filtering use separate classifiers to make pointwise decisions about the tree; they label tokens with roles such as root, leaf, or attaches-tothe-left, and then filter arcs accordingly. Because these classifiers overlap substantially in their filtering consequences, we propose to train them jointly, so that each classifier can focus on the gaps of the others. ...

    pdf6p hongdo_1 12-04-2013 24 2   Download

  • This paper introduces an unsupervised vector approach to disambiguate words in biomedical text that can be applied to all-word disambiguation. We explore using contextual information from the Unified Medical Language System (UMLS) to describe the possible senses of a word. We experiment with automatically creating individualized stoplists to help reduce the noise in our dataset. We compare our results to SenseClusters and Humphrey et al. (2006) using the NLM-WSD dataset and with SenseClusters using conflated data from the 2005 Medline Baseline. ...

    pdf6p hongphan_1 15-04-2013 19 2   Download

  • Reading proficiency is a fundamental component of language competency. However, finding topical texts at an appropriate reading level for foreign and second language learners is a challenge for teachers. This task can be addressed with natural language processing technology to assess reading level. Existing measures of reading level are not well suited to this task, but previous work and our own pilot experiments have shown the benefit of using statistical language models.

    pdf8p bunbo_1 17-04-2013 28 2   Download

  • A term-list is a list of content words that characterize a consistent text or a concept. This paper presents a new method for translating a term-list by using a corpus in the target language. The method first retrieves alternative translations for each input word from a bilingual dictionary. It then determines the most 'coherent' combination of alternative translations, where the coherence of a set of words is defined as the proximity among multi-dimensional vectors produced from the words on the basis of co-occurrence statistics. ...

    pdf5p bunrieu_1 18-04-2013 22 2   Download

  • Collocational word similarity is considered a source of text cohesion that is hard to measure and quantify. The work presented here explores the use of information from a training corpus in measuring word similarity and evaluates the method in the text segmentation task. An implementation, the V e c T i l e system, produces similarity curves over texts using pre-compiled vector representations of the contextual behavior of words. The performance of this system is shown to improve over that of the purely string-based TextTiling algorithm (Hearst, 1997). 1 Background ...

    pdf5p bunrieu_1 18-04-2013 26 2   Download

  • We explore how active learning with Support Vector Machines works well for a non-trivial task in natural language processing. We use Japanese word segmentation as a test case. In particular, we discuss how the size of a pool affects the learning curve. It is found that in the early stage of training with a larger pool, more labeled examples are required to achieve a given level of accuracy than those with a smaller pool. In addition, we propose a novel technique to use a large number of unlabeled examples effectively by adding them gradually to a pool. ...

    pdf8p bunmoc_1 20-04-2013 19 2   Download

  • A novel plasmid vector pSELECT-1 is described which can be used for highly efficient site-directed in vitro mutagenesis. The mutagenesis method is based on the use of single-stranded DNA and two primers, one mutagenic primer and a second correction primer which corrects a defect in the ampicillin resistance gene on the vector and reverts the vector to ampicillin resistance. Using T4 DNA polymerase and T4 DNA ligase the two primers are physically linked on the template. The non-mutant DNA strand is selected against by growth in the presence of ampicillin.

    pdf5p zingzing09 24-04-2013 23 2   Download

  • Generalized Vector Space Models (GVSM) extend the standard Vector Space Model (VSM) by embedding additional types of information, besides terms, in the representation of documents. An interesting type of information that can be used in such models is semantic information from word thesauri like WordNet. Previous attempts to construct GVSM reported contradicting results. The most challenging problem is to incorporate the semantic information in a theoretically sound and rigorous manner and to modify the standard interpretation of the VSM.

    pdf9p bunthai_1 06-05-2013 14 2   Download

  •  An Adenovirus Vector-Mediated Reverse Genetics System for Influenza A Virus Generation established an alternative reverse genetics system for influenza virus generation by using an adenovirus vector (AdV)  which achieves highly efficient gene transfer independent of cell transfection efficiency.

    pdf4p thuyancn 01-06-2015 10 3   Download

  • High-Level Recombinant Protein Production in CHO Cells Using Lentiviral Vectors and the Cumate Gene-Switch developed  an efficient system to generate in less than 2 months, starting from the cDNA, pools of CHO cells stably expressing high-level of recombinant  proteins. It is based on lentiviral vectors (LVs) for stable transduction coupled with the cumate gene-switch for inducible and efficient gene expression.

    pdf13p thuyancn 01-06-2015 14 3   Download

  • In this paper we show how to train statistical machine translation systems on reallife tasks using only non-parallel monolingual data from two languages. We present a modification of the method shown in (Ravi and Knight, 2011) that is scalable to vocabulary sizes of several thousand words. On the task shown in (Ravi and Knight, 2011) we obtain better results with only 5% of the computational effort when running our method with an n-gram language model.

    pdf9p nghetay_1 07-04-2013 16 1   Download

  • Lyric-based song sentiment classification seeks to assign songs appropriate sentiment labels such as light-hearted and heavy-hearted. Four problems render vector space model (VSM)-based text classification approach ineffective: 1) Many words within song lyrics actually contribute little to sentiment; 2) Nouns and verbs used to express sentiment are ambiguous; 3) Negations and modifiers around the sentiment keywords make particular contributions to sentiment;

    pdf4p hongphan_1 15-04-2013 15 1   Download


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