Search results for "methodologies"
showing 10 items of 2106 documents
Generalized SCODEF Deformations on Subdivision Surfaces
2006
This paper proposes to define a generalized SCODEF deformation method on a subdivision surface. It combines an “easy-to-use” free-form deformation with a Loop subdivision algorithm. The deformation method processes only on vertices of an object and permits the satisfaction of geometrical constraints given by the user. The method controls the resulting shape, defining the range (i.e. the impact) of the deformation on an object before applying it. The deformation takes into account the Loop properties to follow the subdivision scheme, allowing the user to fix some constraints at the subdivision-level he works on and to render the final object at the level he wants to. We also propose an adapt…
Lossless and near-lossless image compression based on multiresolution analysis
2013
There are applications in data compression, where quality control is of utmost importance. Certain features in the decoded signal must be exactly, or very accurately recovered, yet one would like to be as economical as possible with respect to storage and speed of computation. In this paper, we present a multi-scale data-compression algorithm within Harten's interpolatory framework for multiresolution that gives a specific estimate of the precise error between the original and the decoded signal, when measured in the L"~ and in the L"p (p=1,2) discrete norms. The proposed algorithm does not rely on a tensor-product strategy to compress two-dimensional signals, and it provides a priori bound…
Statistical Modeling of Huffman Tables Coding
2005
An innovative algorithm for automatic generation of Huffman coding tables for semantic classes of digital images is presented. Collecting statistics over a large dataset of corresponding images, we generated Huffman tables for three images classes: landscape, portrait and document. Comparisons between the new tables and the JPEG standard coding tables, using also different quality settings, have shown the effectiveness of the proposed strategy in terms of final bit size (e.g. compression ratio).
Multimessenger search for sources of gravitational waves and high-energy neutrinos: Initial results for LIGO-Virgo and IceCube
2014
Made available in DSpace on 2022-04-29T07:21:49Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-11-17 We report the results of a multimessenger search for coincident signals from the LIGO and Virgo gravitational-wave observatories and the partially completed IceCube high-energy neutrino detector, including periods of joint operation between 2007-2010. These include parts of the 2005-2007 run and the 2009-2010 run for LIGO-Virgo, and IceCube's observation periods with 22, 59 and 79 strings. We find no significant coincident events, and use the search results to derive upper limits on the rate of joint sources for a range of source emission parameters. For the optimistic assumption of …
Læreres opplevelse av kvalitet i digitale hjelpemidler
2021
Master's thesis in Multimedia and educational technology (MM500)
Digitalt læringsspill som verktøyfor nybegynnende trommeslagere
2020
Master's thesis in Multimedia and educational technology (MM500)
A case study on feature sensitivity for audio event classification using support vector machines
2016
Automatic recognition of multiple acoustic events is an interesting problem in machine listening that generalizes the classical speech/non-speech or speech/music classification problem. Typical audio streams contain a diversity of sound events that carry important and useful information on the acoustic environment and context. Classification is usually performed by means of hidden Markov models (HMMs) or support vector machines (SVMs) considering traditional sets of features based on Mel-frequency cepstral coefficients (MFCCs) and their temporal derivatives, as well as the energy from auditory-inspired filterbanks. However, while these features are routinely used by many systems, it is not …
Quantification and classification of high-resolution magic angle spinning data for brain tumor diagnosis.
2007
The goal of this work is to propose a complete protocol (preprocessing, processing and classification) for classifying brain tumors with proton high-resolution magic-angle spinning ((1)H HR-MAS) data. The different steps of the procedure are detailed and discussed. Feature extraction techniques such as peak integration, including also the automated quantitation method AQSES, were combined with linear (LDA) and non-linear (least-squares support vector machine or LS-SVM) classifiers. Classification accuracy was assessed using a stratified random sampling scheme. The results suggest that LS-SVM performs better than LDA while AQSES performs better than the standard peak integration feature extr…
Decision Committee Learning with Dynamic Integration of Classifiers
2000
Decision committee learning has demonstrated spectacular success in reducing classification error from learned classifiers. These techniques develop a classifier in the form of a committee of subsidiary classifiers. The combination of outputs is usually performed by majority vote. Voting, however, has a shortcoming. It is unable to take into account local expertise. When a new instance is difficult to classify, then the average classifier will give a wrong prediction, and the majority vote will more probably result in a wrong prediction. Instead of voting, dynamic integration of classifiers can be used, which is based on the assumption that each committee member is best inside certain subar…
Dynamic Integration of Decision Committees
2000
Decision committee learning has demonstrated outstanding success in reducing classification error with an ensemble of classifiers. In a way a decision committee is a classifier formed upon an ensemble of subsidiary classifiers. Voting, which is commonly used to produce the final decision of committees has, however, a shortcoming. It is unable to take into account local expertise. When a new instance is difficult to classify, then it easily happens that only the minority of the classifiers will succeed, and the majority voting will quite probably result in a wrong classification. We suggest that dynamic integration of classifiers is used instead of majority voting in decision committees. Our…