Search results for "Descriptor"
showing 10 items of 144 documents
Description de la typicite aromatique de vins de bourgogne issus du cepage chardonnay
1993
<p style="text-align: justify;">La typicité aromatique de 23 vins blancs de Bourgogne issus du cépage Chardonnay est évaluée par 32 oenologues au cours de 3 séances. De manière indépendante, une caractérisation de l'odeur et de l'arôme de chaque vin est fournie par chaque sujet sous la forme d'un choix libre de 5 descripteurs au plus.</p><p style="text-align: justify;">Les vins se répartissent selon 3 groupes de typicité croissante sans rapport net avec les appellations. Sept descripteurs-clefs de l'odeur et de l'arôme du Chardonnay de Bourgogne s'imposent: miel, vanille, pain grillé, beurre frais, boisé, floral et noisette. De plus, une liste de 9 autres descripteurs auxi…
Rethinking the sGLOH Descriptor
2018
sGLOH (shifting GLOH) is a histogram-based keypoint descriptor that can be associated to multiple quantized rotations of the keypoint patch without any recomputation. This property can be exploited to define the best distance between two descriptor vectors, thus avoiding computing the dominant orientation. In addition, sGLOH can reject incongruous correspondences by adding a global constraint on the rotations either as an a priori knowledge or based on the data. This paper thoroughly reconsiders sGLOH and improves it in terms of robustness, speed and descriptor dimension. The revised sGLOH embeds more quantized rotations, thus yielding more correct matches. A novel fast matching scheme is a…
Computational identification of chemical compounds with potential anti-Chagas activity using a classification tree
2021
Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action. A large dataset of 584 compounds, obtained from the Drugs for Neglected Diseases initiative, was selected to develop the computational model. Dragon software was used to calculate the molecular descriptors and WEKA software to obtain the classification tree. The best model shows accuracy greater than 93.4% for the training set; the tree was also validated using a 10-fold cross-validation p…
Approximated overlap error for the evaluation of feature descriptors on 3D scenes
2013
This paper presents a new framework to evaluate feature descriptors on 3D datasets. The proposed method employs the approximated overlap error in order to conform with the reference planar evaluation case of the Oxford dataset based on the overlap error. The method takes into account not only the keypoint centre but also the feature shape and it does not require complex data setups, depth maps or an accurate camera calibration. Only a ground-truth fundamental matrix should be computed, so that the dataset can be freely extended by adding further images. The proposed approach is robust to false positives occurring in the evaluation process, which do not introduce any relevant changes in the …
Multimodal Images Classification using Dense SURF, Spectral Information and Support Vector Machine
2019
International audience; The multimodal image classification is a challenging area of image processing which can be used to examine the wall painting in the cultural heritage domain. In such classification, a common space of representation is important. In this paper, we present a new method for multimodal representation learning, by using a pixel-wise feature descriptor named dense Speed Up Robust Features (SURF) combined with the spectral information carried by the pixel. For classification of extracted features we have used support vector machine (SVM). Our database was extracted from acquisition on cultural heritage wall paintings that contain four modalities UV, Visible, IRR and fluores…
A Dual Taxonomy for Defects in Digitized Historical Photos
2009
Old photos may be affected by several types of defects. Manual restorers use their own taxonomy to classify damages by which a photo is affected, in order to apply the proper restoration techniques for a specific defect. Once a photo is digitally acquired, defects become part of the image, and their aspect change. This paper wants to be a first attempt to correlate real defects of printed photos, and digital defects of their digitized versions. A dual taxonomy is proposed, for real and digital defects, and used to classify an image dataset, for a posteriori comparative study. Furthermore, a set of digital features is analyzed for digitized images, to identify which of them could be useful f…
Advances in the statistical methodology for the selection of image descriptors for visual pattern representation and classification
1995
Recent advances in the statistical methodology for selecting optimal subsets of features (image descriptors) for visual pattern representation and classification are presented. The paper attempts to provide a guideline about which approach to choose with respect to the a priori knowledge of the problem. Two basic approaches are reviewed and the conditions under which they should be used are specified. References to more detailed material about each one of the methods are given and experimental results supporting the main conclusions are briefly outlined.
Statistical Reconstruction of Microstructures Using Entropic Descriptors
2018
We report a multiscale approach of broad applicability to stochastic reconstruction of multiphase materials, including porous ones. The approach devised uses an optimization method, such as the simulated annealing (SA) and the so-called entropic descriptors (EDs). For a binary pattern, they quantify spatial inhomogeneity or statistical complexity at discrete length-scales. The EDs extract dissimilar structural information to that given by two-point correlation functions (CFs). Within the SA, we use an appropriate cost function consisting of EDs or comprised of EDs and CFs. It was found that the stochastic reconstruction is computationally efficient when we begin with a preliminary synthetic…
Set Descriptors for Visual Evaluation of Human Corneal Endothelia
2001
Images of corneal endothelium obtained from specular microscopy are of great importance in the evaluation of the corneal endothelium status. Several commercial tools provide some numerical descriptors to characterize these images in terms of cell density, hexagonality, and some descriptive statistics of the cell areas. However, it is a too simple analysis that only detects severe abnormal endothelia with many irregular and large cells. Detection of subtle abnormalities needs a more refined analysis. This paper proposes a shape-size descriptor based on some modified versions of the geometric covariogram. This descriptor is presented as a valid alternative to the classical analysis that provi…
Multivariate analysis in the identification of biological targets for designed molecular structures: The BIOTA protocol
2013
In this work the new protocol BIOlogical Target Assignation (BIOTA) for the prediction of the biological target from molecular structures is proposed. BIOTA is based on the Principal Components Analysis (PCA) application on a matrix of ligands versus molecular descriptors. The application of BIOTA could allow to hypothesize the mechanism of action of a candidate drug prior to its biological evaluation or to repurpose old drugs. The protocol can be fine-tuned by choosing opportune targets (biological or not) and molecular descriptors, and it can be useful in every fields in with it is possible to collect set of compounds with known properties. The robustness of the protocol depends from diff…