Search results for " recognition"
showing 10 items of 3220 documents
Reliable polygonal approximations of imaged real objects through dominant point detection
1998
Abstract The problem of dominant point detection is posed, taking into account what usually happens in practice. The algorithms found in the literature often prove their performance with laboratory contours, but the shapes in real images present noise, quantization, and high inter and intra-shape variability. These effects are analyzed and solutions to them are proposed. We will also focus on the conditions for an efficient (few points) and precise (low error) dominant point extraction that preserves the original shape. A measurement of the committed error (optimization error, E 0 ) that takes into account both aspects is defined for studying this feature.
Hop: Histogram of patterns for human action representation
2017
This paper presents a novel method for representing actions in terms of multinomial distributions of frequent sequential patterns of different length. Frequent sequential patterns are series of data descriptors that occur many times in the data. This paper proposes to learn a codebook of frequent sequential patterns by means of an apriori-like algorithm, and to represent an action with a Bag-of-Frequent-Sequential-Patterns approach. Preliminary experiments of the proposed method have been conducted for action classification on skeletal data. The method achieves state-of-the-art accuracy value in cross-subject validation.
Selective and Efficient Removal of Mercury from Aqueous Media with the Highly Flexible Arms of a BioMOF
2016
A robust and water-stable metal-organic framework (MOF), featuring hexagonal channels decorated with methionine residues (1), selectively captures toxic species such as CH3 Hg(+) and Hg(2+) from water. 1 exhibits the largest Hg(2+) uptake capacity ever reported for a MOF, decreasing the [Hg(2+) ] and [CH3 Hg(+) ] concentrations in potable water from highly hazardous 10 ppm to the much safer values of 6 and 27 ppb, respectively. Just like with biological systems, the high-performance metal capture also involves a molecular recognition process. Both CH3 Hg(+) and Hg(2+) are efficiently immobilized by specific conformations adopted by the flexible thioether "claws" decorating the pores of 1. T…
Induced-Fit Molecular Recognition with Water-Soluble Cavitands
2000
Synthesis of novel water-soluble cavitands 1 and 2 and their complexes—the caviplexes—is described. The solubility in water derives from four primary ammonium groups on the lower rim and eight secondary amide groups on the upper rim. Cavitands 1 and 2 exist as D2d velcraplex dimers in aqueous solution but the addition of lipophilic guests 15–24 induces conformational changes to the vase-like structures. The internal cavity dimensions are 8×10 A, and the exchange rates of guests in the caviplexes are slow on the NMR timescale (room temperature and 600 MHz). The direct observation of bound species and the stoichiometry of the complexes is reported. The association constants (Ka) between 0.4×1…
Color degradation mapping of rock art paintings using microfading spectrometry
2021
[EN] Rock art documentation is a complex task that should be carried out in a complete, rigorous and exhaustive way, in order to take particular actions that allow stakeholders to preserve the archaeological sites under constant deterioration. The pigments used in prehistoric paintings present high light sensitivity and rigorous scientific color degradation mapping is not usually undertaken in overall archaeological sites. Microfading spectrometry is a suitable technique for determining the light-stability of pigments found in rock art paintings in a non-destructive way. Spectral data can be transformed into colorimetric information following the recommendations published by the Commission …
Mosaic floors of roman Villa del Casale: Principal component analysis on spectrophotometric and colorimetric data
2013
Abstract Spectrophotometric and colorimetric data obtained during a measurement campaign aimed at supporting the Roman "Villa del Casale" (Piazza Armerina, Sicily, Italy) conservation activities, are presented. Special attention was paid to the possible variation of the chromatic coordinates, possibly due to the interventions of cleaning, consolidation, and protection. Data have been analyzed by the Principal Component Analysis (PCA) statistical technique, with the attempt to investigate its role in data variability reduction and verify its effectiveness in interpreting the phenomena occurring on the mosaic surface of the Villa, through grouping the observations into homogenous clusters. Ef…
Study of the performance of a resolution criterion to characterise complex chromatograms with unknowns or without standards
2017
The search for best conditions in liquid chromatography is routinely carried out with information provided by chemical standards. However, sometimes there are samples with insufficient knowledge about their chemical composition. In other cases, identities of the components are known, but there are no standards available, and in other cases the identities of peaks in chromatograms taken under different conditions are ambiguous. Most resolution criteria used to measure separation performance cannot be applied to these samples. In this work, a global resolution function valid for all situations was developed based on automatic measurements of peak prominences (area fraction exceeding the line …
Comparison of Micro X-ray Computer Tomography Image Segmentation Methods: Artificial Neural Networks Versus Least Square Support Vector Machine
2013
Micro X-ray computer tomography (XCT) is a powerful non-destructive method for obtaining information about rock structures and mineralogy. A new methodology to obtain porosity from 2D XCT digital images using artificial neural network and least square support vector machine is demonstrated following these steps: the XCT image was first preprocessed, thereafter clustering algorithms such as K-means, Fuzzy c-means and self-organized maps was used for image segmentation. Then artificial neural network was applied for image classification. For comparison, least square support vector machine approach was used for classification labeling of the scan images. The methodology shows how artificial ne…
Fuzzy C-Means Segmentation on Brain MR Slices Corrupted by RF-Inhomogeneity
2007
Brain MR Images corrupted by RF-Inhomogeneity exhibit brightness variations in such a way that a standard Fuzzy C-Means (fcm) segmentation algorithm fails. As a consequence, modified versions of the algorithm can be found in literature, which take into account the artifact. In this work we show that the application of a suitable pre-processing algorithm, already presented by the authors, followed by a standard fcm segmentation achieves good results also. The experimental results ones are compared with those obtained using SPM5, which can be considered the state of the art algorithm oriented to brain segmentation and bias removal.
Online detection and removal of eye blink artifacts from electroencephalogram
2021
Abstract The most prominent type of artifact contaminating electroencephalogram (EEG) signals are the eye blink (EB) artifacts, which could potentially lead to misinterpretation of the EEG signal. Online identification and elimination of eye blink artifacts are crucial in applications such a Brain-Computer Interfaces (BCI), neurofeedback, and epilepsy diagnosis. In this paper, algorithms that combine unsupervised eye blink artifact detection (eADA) with modified Empirical Mode Decomposition (FastEMD) and Canonical Correlation Analysis (CCA) are proposed, i.e., FastEMD-CCA2 and FastCCA, to automatically identify eye blink artifacts and remove them in an online setting. The average accuracy, …