Search results for "Data type"
showing 10 items of 1183 documents
Inverse procedural modeling of 3D models for virtual worlds
2016
This course presents a collection of state-of-the-art approaches for modeling and editing of 3D models for virtual worlds, simulations, and entertainment, in addition to real-world applications. The first contribution of this course is a coherent review of inverse procedural modeling (IPM) (i.e., proceduralization of provided 3D content). We describe different formulations of the problem as well as solutions based on those formulations. We show that although the IPM framework seems under-constrained, the state-of-the-art solutions actually use simple analogies to convert the problem into a set of fundamental computer science problems, which are then solved by corresponding algorithms or opt…
Active Learning Methods for Efficient Hybrid Biophysical Variable Retrieval
2016
Kernel-based machine learning regression algorithms (MLRAs) are potentially powerful methods for being implemented into operational biophysical variable retrieval schemes. However, they face difficulties in coping with large training data sets. With the increasing amount of optical remote sensing data made available for analysis and the possibility of using a large amount of simulated data from radiative transfer models (RTMs) to train kernel MLRAs, efficient data reduction techniques will need to be implemented. Active learning (AL) methods enable to select the most informative samples in a data set. This letter introduces six AL methods for achieving optimized biophysical variable estimat…
Online Non-linear Topology Identification from Graph-connected Time Series
2021
Estimating the unknown causal dependencies among graph-connected time series plays an important role in many applications, such as sensor network analysis, signal processing over cyber-physical systems, and finance engineering. Inference of such causal dependencies, often know as topology identification, is not well studied for non-linear non-stationary systems, and most of the existing methods are batch-based which are not capable of handling streaming sensor signals. In this paper, we propose an online kernel-based algorithm for topology estimation of non-linear vector autoregressive time series by solving a sparse online optimization framework using the composite objective mirror descent…
Accurate Graph Filtering in Wireless Sensor Networks
2020
Wireless sensor networks (WSNs) are considered as a major technology enabling the Internet of Things (IoT) paradigm. The recent emerging Graph Signal Processing field can also contribute to enabling the IoT by providing key tools, such as graph filters, for processing the data associated with the sensor devices. Graph filters can be performed over WSNs in a distributed manner by means of a certain number of communication exchanges among the nodes. But, WSNs are often affected by interferences and noise, which leads to view these networks as directed, random and time-varying graph topologies. Most of existing works neglect this problem by considering an unrealistic assumption that claims the…
Iterative Reconstruction of Signals on Graph
2020
We propose an iterative algorithm to interpolate graph signals from only a partial set of samples. Our method is derived from the well known Papoulis-Gerchberg algorithm by considering the optimal value of a constant involved in the iteration step. Compared with existing graph signal reconstruction algorithms, the proposed method achieves similar or better performance both in terms of convergence rate and computational efficiency.
Sputtered SiOxNy thin films: improving optical efficiency of liquid crystal diffuser elements in multi-focal near-to-eye display architecture
2021
In this work we present reactive sputtered SiOxNy films with a variable refractive index as a convienent solution for contrast improvement of liquid crystal diffuser multi stacks in near-to-eye AR/VR displays. The focus concerns minimization of light reflections between internal structures, in particular ITO, by optimizing internal layers through tailored properties of thin film coatings, as well as subsequent laser patterning of thin film stack. Inorganic thin films have been deposited on glass by physical vapor deposition. Corresponding refractive index, thickness, uniformity and dielectric characteristics and other electro-optical properties have been measured and their impact on the res…
Links and Bifurcations in Nonsingular Morse–Smale Systems
1997
Wada's theorem classifies the set of periodic orbits in NMS systems on S3 as links, that can be written in terms of six operations. This characterization allows us to study the topological restrictions that links require to suffer a given codimension one bifurcation. Moreover, these results are reproduced in the case of NMS systems with rotational symmetries, introducing new geometrical tools.
Algorithms for Graph and Network Analysis: Graph Alignment
2019
In this article we discuss the problem of graph alignment, which has been longly referred to for the purpose of analyzing and comparing biological networks. In particular, we describe different facets of graph alignment, according to the number of input networks, the fixed output objective, the possible heterogeneity of input data. Accordingly, we will discuss pairwise and multiple alignment, global and local alignment, etc. Moreover, we provide a comprehensive overview of the algorithms and techniques proposed in the literature to solve each of the specific considered types of graph alignment. In order to make the material presented here complete and useful to guide the reader in the use o…
Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks
2020
We propose a novel approach for the recommendation of possible customers (users) to advertisers (e.g., brands) based on two main aspects: (i) the comparison between On-line Social Network profiles, and (ii) neighborhood analysis on the On-line Social Network. Profile matching between users and brands is considered based on bag-of-words representation of textual contents coming from the social media, and measures such as the Term Frequency-Inverse Document Frequency are used in order to characterize the importance of words in the comparison. The approach has been implemented relying on Big Data Technologies, allowing this way the efficient analysis of very large Online Social Networks. Resul…
Markov Model for Tweets Geographic Distribution Characterization
2015
Abstract In this paper we will continue our researches regarding e-Business and e-Government modeling on Social Media presented in (Stoica, Pitic, & Mihaescu, 2013). Among message and user parameters we add a new parameter used to describe the geographical dispersion of Twitter messages. This new parameter will characterize the way one set of messages will spread in Social Graph from the physical word point of view. The first model, presented as “A Novel Model for E-Business and E-Government Processes on Social”, will be extended with the geographical parameter PG. We will define and we will describe the Markov Model used to organize the messages gathered from social media. The main idea of…