Search results for "cluster [track data analysis]"

Shared feature representations of LiDAR and optical images: Trading sparsity for semantic discrimination

2015

This paper studies the level of complementary information conveyed by extremely high resolution LiDAR and optical images. We pursue this goal following an indirect approach via unsupervised spatial-spectral feature extraction. We used a recently presented unsupervised convolutional neural network trained to enforce both population and lifetime spar-sity in the feature representation. We derived independent and joint feature representations, and analyzed the sparsity scores and the discriminative power. Interestingly, the obtained results revealed that the RGB+LiDAR representation is no longer sparse, and the derived basis functions merge color and elevation yielding a set of more expressive…

Cluster analysis for cavity detection using seismic refraction and electrical resistivity tomography

2017

Geophysical methods (in particular ERT technique) constitute an excellent tool for the detection of buried cavities. However the integration approach of e different geophysical methods could minimize the ambiguity of geophysical interpretation of the buried cavity. The technique of electrical tomography has been joined to the technique of seismic refraction tomography in order to obtain more robust interpretations. Many tests have been carried out using synthetic data and experimental ones. It was finally used a statistical approach based on cluster analysis of the P-wave velocity, the density of the seismic rays and the electrical resistivity of the synthetic and experimental models. Distr…

Proanthocyanidins and Where to Find Them: A Meta-Analytic Approach to Investigate Their Chemistry, Biosynthesis, Distribution, and Effect on Human He…

2021

Proanthocyanidins (PACs) are a class of polyphenolic compounds that are attracting considerable interest in the nutraceutical field due to their potential health benefits. However, knowledge about the chemistry, biosynthesis, and distribution of PACs is limited. This review summarizes the main chemical characteristics and biosynthetic pathways and the main analytical methods aimed at their identification and quantification in raw plant matrices. Furthermore, meta-analytic approaches were used to identify the main plant sources in which PACs were contained and to investigate their potential effect on human health. In particular, a cluster analysis identified PACs in 35 different plant famili…

A fully automatic method for biological target volume segmentation of brain metastases

2016

Leksell Gamma Knife is a mini-invasive technique to obtain a complete destruction of cerebral lesions delivering a single high dose radiation beam. Positron Emission Tomography (PET) imaging is increasingly utilized for radiation treatment planning. Nevertheless, lesion volume delineation in PET datasets is challenging because of the low spatial resolution and high noise level of PET images. Nowadays, the biological target volume (BTV) is manually contoured on PET studies. This procedure is time expensive and operator-dependent. In this article, a fully automatic algorithm for the BTV delineation based on random walks (RW) on graphs is proposed. The results are compared with the outcomes of…

Integration of HVSR measures and stratigraphic constraints for seismic microzonation studies: the case of Oliveri (ME)

2014

Abstract. Because of its high seismic hazard the urban area of Oliveri has been subject of first level seismic microzonation. The town develops on a large coastal plain made of mixed fluvial/marine sediments, overlapping a complexly deformed substrate. In order to identify points on the area probably suffering relevant site effects and define a preliminary Vs subsurface model for the first level of microzonation, we performed 23 HVSR measurements. A clustering technique of continuous signals has been used to optimize the calculation of the HVSR curves. 42 reliable peaks of the H/V spectra in the frequency range 0.6–10 Hz have been identified. A second clustering technique has been applied t…

Geometric and morphologic evolution of normal fault planes and traces from 2D to 4D data

2003

Abstract The detailed 3D geometry of normal fault planes is described and analysed using datasets from outcrop studies (2D), seismic surveys (3D) and analogue models (4D). Different geometric configurations of simple isolated normal faults are studied by reference to processes of normal fault propagation. When a normal fault propagates without interacting with other fault zones, the entire border of the principal plane displays characteristic connected secondary structures. These secondary structures cause bifurcations of the principal fault terminations. The along-strike terminations of the principal plane display typical bifurcation configurations (‘ear geometry‘). The orientation of the …

Pattern Classification from Multi-beam Acoustic Data Acquired in Kongsfjorden

2021

Climate change is causing a structural change in Arctic ecosystems, decreasing the effectiveness that the polar regions have in cooling water masses, with inevitable repercussions on the climate and with an impact on marine biodiversity. The Svalbard islands under study are an area greatly influenced by Atlantic waters. This area is undergoing changes that are modifying the composition and distribution of the species present. The aim of this work is to provide a method for the classification of acoustic patterns acquired in the Kongsfjorden, Svalbard, Arctic Circle using multibeam technology. Therefore the general objective is the implementation of a methodology useful for identifying the a…

INVESTIGATION, REALIZATION, AND ENTANGLEMENT CHARACTERIZATION OF COMPLEX OPTICAL QUANTUM STATES

2020

Multi-modal Image Registration Using Fuzzy Kernel Regression

2009

This paper presents a study aimed to the realization of a novel multiresolution registration framework. The transformation function is computed iteratively as a composition of local deformations determined by the maximization of mutual information. At each iteration, local transformations are joint together using fuzzy kernel regression. This technique represents the core of the mothod and it's formally described from a probabilistic perspective. It avoids blocking artifacts and allows to keep the final deformation spatially congruent and smooth. Both qualitative and quantitative experimental results show that this approach is equally effective for registering datasets acquired from both si…

Selecting significant respondents from large audience datasets: The case of the World Hobbit Project

2016

International projects, online questionnaires, or data mining techniques now allow audience researchers to gather very large and complex datasets. But whilst data collection capacity is hugely growing, qualitative analysis, conversely, becomes increasingly difficult to conduct. In this paper, I suggest a strategy that might allow the researcher to manage this complexity. The World Hobbit Project dataset (36,109 cases), including answers to both closed and open-ended questions, was used for this purpose. The strategy proposed here is based on between-methods sequential triangulation, and tries to combine statistical techniques (k-means clustering) with textual analysis. K-means clustering pe…