<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fogel, P.</style></author><author><style face="normal" font="default" size="100%">Gobinet, C.</style></author><author><style face="normal" font="default" size="100%">Young, S.S.</style></author><author><style face="normal" font="default" size="100%">Zugaj, D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluation of unmixing methods for the separation of Quantum Dot sources</style></title><secondary-title><style face="normal" font="default" size="100%">Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS ’09. First Workshop on</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bayesian methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Bayesian positive source separation</style></keyword><keyword><style  face="normal" font="default" size="100%">BPSS</style></keyword><keyword><style  face="normal" font="default" size="100%">cadmium compounds</style></keyword><keyword><style  face="normal" font="default" size="100%">CdSe</style></keyword><keyword><style  face="normal" font="default" size="100%">consensus nonnegative matrix factorization</style></keyword><keyword><style  face="normal" font="default" size="100%">Fluorescence</style></keyword><keyword><style  face="normal" font="default" size="100%">hyperspectral images</style></keyword><keyword><style  face="normal" font="default" size="100%">Hyperspectral imaging</style></keyword><keyword><style  face="normal" font="default" size="100%">hyperspectral system</style></keyword><keyword><style  face="normal" font="default" size="100%">ICA</style></keyword><keyword><style  face="normal" font="default" size="100%">II-VI semiconductors</style></keyword><keyword><style  face="normal" font="default" size="100%">independent component analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Nanobioscience</style></keyword><keyword><style  face="normal" font="default" size="100%">Nanocrystals</style></keyword><keyword><style  face="normal" font="default" size="100%">nanometer dimensions</style></keyword><keyword><style  face="normal" font="default" size="100%">NMF</style></keyword><keyword><style  face="normal" font="default" size="100%">Photonic crystals</style></keyword><keyword><style  face="normal" font="default" size="100%">Probes</style></keyword><keyword><style  face="normal" font="default" size="100%">quantum dot sources</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantum dots</style></keyword><keyword><style  face="normal" font="default" size="100%">semiconductor crystals</style></keyword><keyword><style  face="normal" font="default" size="100%">semiconductor quantum dots</style></keyword><keyword><style  face="normal" font="default" size="100%">Source separation</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial localization</style></keyword><keyword><style  face="normal" font="default" size="100%">ultraviolet spectra</style></keyword><keyword><style  face="normal" font="default" size="100%">unmixing methods</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><pages><style face="normal" font="default" size="100%">1-4</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4244-4686-5</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Quantum Dots (QDs) are semiconductor crystals with nanometer dimensions, which have fluorescence properties that can be adjusted through controlling their diameter. Under ultraviolet light excitation, these nanocrystals re-emit photons in the visible spectrum, with a wavelength ranging from red to blue as their size diminishes. We created an experiment to evaluate unmixing methods for hyperspectral images. The wells of a matrix [3 times 3] were filled with individual or up to three of five QDs. The matrix was imaged by a hyperspectral system (Photon Etc., Montreal, QC, CA) and a data ldquocuberdquo of 512 rows times 512 columns times 63 wavelengths was generated. For unmixing, we tested three approaches: independent component analysis (ICA), Bayesian positive source separation (BPSS) and our new consensus non-negative matrix factorization (CNFM) method. For each of these methods, we assessed the ability to separate the different sources from both spectral and spatial localization points of view. In this situation, we showed that BPSS and CNMF model estimates were very close to the original design of our experiment and were better than the ICA results. However, the time needed for the BPSS model to converge is substantially higher than CNMF. In addition, we show how the CNMF coefficients can be used to provide reasonable bounds for the number of sources, a key issue for unmixing methods, and allow for an effective segmentation of the spatial signal.&lt;/p&gt;
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