Search results for " Text"
showing 10 items of 836 documents
Linear-size suffix tries
2016
Suffix trees are highly regarded data structures for text indexing and string algorithms [MCreight 76, Weiner 73]. For any given string w of length n = | w | , a suffix tree for w takes O ( n ) nodes and links. It is often presented as a compacted version of a suffix trie for w, where the latter is the trie (or digital search tree) built on the suffixes of w. Here the compaction process replaces each maximal chain of unary nodes with a single arc. For this, the suffix tree requires that the labels of its arcs are substrings encoded as pointers to w (or equivalent information). On the contrary, the arcs of the suffix trie are labeled by single symbols but there can be Θ ( n 2 ) nodes and lin…
L'estrazione automatica dei ruoli semantici corradicali. The importance of being Cognate
2022
This study will introduce a tool – termed NLPYTALY – for the automatictreatment of naturally-occurring texts in Italian. The tool distinguishesconstructs with an ordinary verb from those with a support verb. Mean-ing is rendered by using cognate (i.e. etymologically related) semantic roles (CSR), which differ from other roles because they are expressed withthe content morpheme of the predicate licensing arguments. CSRs offer anumber of advantages: they can be semi-automatically derived and use the who-does-what model. Besides, they facilitate the detection of anaphoric chains and produce a foreground/background opposition of the namedentities. Finally, they permit the construction of a chro…
A Predictive System to Classify Preoperative Grading of Rectal Cancer Using Radiomics Features
2022
Although preoperative biopsy of rectal cancer (RC) is an essential step for confirmation of diagnosis, it currently fails to provide prognostic information to the clinician beyond a rough estimation of tumour grade. In this study we used a risk classification to stratified patient in low-risk and high-risk patients in relation to the disease free survival and the overall survival using histopathological post-operative features. The purpose of this study was to evaluate if low-risk and high-risk RC can be distinguished using a CT-based radiomics model. We retrospectively reviewed the preoperative abdominal contrast-enhanced CT of 40 patients with RC. CT portal-venous phase was used for manua…
Complex networks : application for texture characterization and classification
2008
This article describes a new method and approch of texture characterization. Using complex network representation of an image, classical and derived (hierarchical) measurements, we presente how to have good performance in texture classification. Image is represented by a complex networks : one pixel as a node. Node degree and clustering coefficient, using with traditionnal and extended hierarchical measurements, are used to characterize ”organisation” of textures.
Constitutive Models for the Tensile Behaviour of TRM Materials: Literature Review and Experimental Verification
2021
In recent years, the scientific community has focused its interest on innovative inorganic matrix composite materials, namely TRM (Textile Reinforced Mortar). This class of materials satisfies the need of retrofitting existing masonry buildings, by keeping the compatibility with the substrate. Different recent studies were addressed to improve the knowledge on their mechanical behaviour and some theoretical models were proposed for predicting the tensile response of TRM strips. However, this task is complex due to the heterogeneity of the constituent materials and the stress transfer mechanism developed between matrix and fabric through the interface in the cracked stage. This paper present…
A new image segmentation approach using community detection algorithms
2015
Image segmentation has an important role in many image processing applications. Several methods exist for segmenting an image. However, this technique is still a relatively open topic for which various research works are regularly presented. With the recent developments on complex networks theory, image segmentation techniques based on graphs has considerably improved. In this paper, we present a new perspective of image segmentation, by applying three of the most efficient community detection algorithms, Louvain, infomap and stability optimization based on the louvain algorithm, and we extract communities in which the highest modularity feature is achieved. After we show that this measure …
Extracting cloud motion from satellite image sequences
2004
This paper present a new technique for the estimation of cloud motion, using a sequence of infrared satellite images. It can be considered a challenging task due to the complexity of phenomena implied, as non-linear events and a non-rigid motion. In this circumstances most motion models are not suitable and new algorithms have to be developed. We propose a novel method, combining an Automatic Multilevel Thresholding for image segmentation, a Block Matching Algorithm (BMA) and a best candidate block search along with a vector median regularization.
Editorial: Mining Scientific Papers: NLP-enhanced Bibliometrics
2019
International audience
Image Recognition through Incremental Discriminative Common Vectors
2010
An incremental approach to the discriminative common vector (DCV) method for image recognition is presented. Two different but equivalent ways of computing both common vectors and corresponding subspace projections have been considered in the particular context in which new training data becomes available and learned subspaces may need continuous updating. The two algorithms are based on either scatter matrix eigendecomposition or difference subspace orthonormalization as with the original DCV method. The proposed incremental methods keep the same good properties than the original one but with a dramatic decrease in computational burden when used in this kind of dynamic scenario. Extensive …
sar: Automatic generation of statistical reports using Stata and Microsoft Word for Windows
2013
The output provided by most Stata commands is plain text not suitable to be presented or published. After the numerical and graphical outputs are obtained, the user has to copy them into a word processor to complete the editing process. Some Stata commands help you to obtain well-formatted output, especially tabulated results in LATEX or other formats, but they are not a complete solution nor are they friendly tools. Stata automatic report (Sar) is an easy-to-use macro for Microsoft Word for Windows that allows a powerful integration between Stata and Word. With Sar, the user can retrieve numerical results and graphs from Stata and automatically insert them into a well-formatted Word docum…