@article{corno_usability_2014,

title = {Usability assessment of the virtual multitasking test (V-MT) for elderly people},

author = {G. Corno and S. Bouchard and H. Forget},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84928056933&partnerID=40&md5=b0e0cc4d1c5203678a24bbdcf36d7686},

issn = {15548716},

year  = {2014},

date = {2014-01-01},

journal = {Annual Review of CyberTherapy and Telemedicine},

volume = {12},

pages = {168–172},

abstract = {In the last decades an increasing number of psychological researches have used Virtual Reality (VR) technology in different fields. Nevertheless, few studies used Virtual Environments (VEs) with a sample of older users. The aim of the present study is to assess the usability of the Virtual Multitasking Test (V-MT), which consists in a virtual apartment created to assess cognitive functions in elderly people. This study reports the preliminary results to support the development of a VE in which elderly people feel present and fully immersed. © 2014, Virtual reality med institute. All rights reserved.},

note = {Publisher: Virtual reality med institute},

keywords = {80 and over, aged, behavior, cognition, cognitive defect, Cognitive Dysfunction, Cognitive functions, computer assisted diagnosis, Computer-Assisted, Diagnosis, Elderly, Elderly people, female, Geriatric Assessment, human, human experiment, Humans, male, Middle Aged, Multitasking, Multitasking Behavior, Older users, Presence, procedures, Psychological research, Usability, Usability assessment, very elderly, virtual reality},

pubstate = {published},

tppubtype = {article}

}

@article{allili_wavelet_2012,

title = {Wavelet modeling using finite mixtures of generalized Gaussian distributions: Application to texture discrimination and retrieval},

author = {M. S. Allili},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859096106&doi=10.1109%2fTIP.2011.2170701&partnerID=40&md5=0420facdc04978ad84bea3126bc1183a},

doi = {10.1109/TIP.2011.2170701},

issn = {10577149},

year  = {2012},

date = {2012-01-01},

journal = {IEEE Transactions on Image Processing},

volume = {21},

number = {4},

pages = {1452–1464},

abstract = {This paper addresses statistical-based texture modeling using wavelets. We propose a new approach to represent the marginal distribution of the wavelet coefficients using finite mixtures of generalized Gaussian (MoGG) distributions. The MoGG captures a wide range of histogram shapes, which provides better description and discrimination of texture than using single probability density functions (pdf's), as proposed by recent state-of-the-art approaches. Moreover, we propose a model similarity measure based on Kullback-Leibler divergence (KLD) approximation using Monte Carlo sampling methods. Through experiments on two popular texture data sets, we show that our approach yields significant performance improvements for texture discrimination and retrieval, as compared with recent methods of statistical-based wavelet modeling. © 2011 IEEE.},

keywords = {algorithm, Algorithms, article, Automated, automated pattern recognition, computer assisted diagnosis, Computer Simulation, Computer-Assisted, Data Interpretation, Finite mixtures, Generalized Gaussian, Generalized Gaussian Distributions, Image Enhancement, Image Interpretation, Image segmentation, Imaging, Kullback Leibler divergence, Marginal distribution, methodology, Mixtures, Models, Monte Carlo methods, Monte Carlo sampling, Normal Distribution, Pattern Recognition, Performance improvements, reproducibility, Reproducibility of Results, Sensitivity and Specificity, Similarity measure, State-of-the-art approach, Statistical, statistical analysis, statistical model, Texture data set, Texture discrimination, Texture modeling, Textures, three dimensional imaging, Three-Dimensional, Wavelet Analysis, Wavelet coefficients, Wavelet decomposition, Wavelet modeling},

pubstate = {published},

tppubtype = {article}

}