Search results for "Signal"

showing 10 items of 6924 documents

In vivo Trafficking and Localization of p24 Proteins in Plant Cells

2008

p24 proteins constitute a family of putative cargo receptors that traffic in the early secretory pathway. p24 proteins can be divided into four subfamilies (p23, p24, p25 and p26) by sequence homology. In contrast to mammals and yeast, most plant p24 proteins contain in their cytosolic C-terminus both a dilysine motif in the -3, -4 position and a diaromatic motif in the -7, -8 position. We have previously shown that the cytosolic tail of Arabidopsis p24 proteins has the ability to interact with ARF1 and coatomer (through the dilysine motif) and with COPII subunits (through the diaromatic motif). Here, we establish the localization and trafficking properties of an Arabidopsis thaliana p24 pr…

Recombinant Fusion ProteinsMolecular Sequence DataArabidopsisGolgi ApparatusVacuoleProtein Sorting SignalsBiologyEndoplasmic ReticulumBiochemistrysymbols.namesakeStructural BiologyArabidopsisGeneticsAnimalsHumansProtein IsoformsAmino Acid SequenceMolecular BiologyCOPIISecretory pathwayArabidopsis ProteinsLysineEndoplasmic reticulumMembrane ProteinsCell BiologyCOPIGolgi apparatusbiology.organism_classificationActinsCell biologyDNA-Binding ProteinsProtein TransportBiochemistryCoatomerVacuolessymbolsCOP-Coated VesiclesCarrier ProteinsTranscription FactorsTraffic
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Automatic recognition of tree species from 3D point clouds of forest plots

2014

The objective of the thesis is the automatic recognition of tree species from Terrestrial LiDAR data. This information is essential for forest inventory. As an answer, we propose different recognition methods based on the 3D geometric texture of the bark.These methods use the following processing steps: a preprocessing step, a segmentation step, a feature extraction step and a final classification step. They are based on the 3D data or on depth images built from 3D point clouds of tree trunks using a reference surface.We have investigated and tested several segmentation approaches on depth images representing the geometric texture of the bark. These approaches have the disadvantages of over…

Reconnaissance de formes 3DInventaire forestierAnalyse de texture 3DTree species recognitionIdentification des espèces d’arbres3D geometric texture analysisForest inventory3D pattern recognition[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Image-based detection and classification of allergenic pollen

2015

The correct classification of airborne pollen is relevant for medical treatment of allergies, and the regular manual process is costly and time consuming. An automatic processing would increase considerably the potential of pollen counting. Modern computer vision techniques enable the detection of discriminant pollen characteristics. In this thesis, a set of relevant image-based features for the recognition of top allergenic pollen taxa is proposed and analyzed. The foundation of our proposal is the evaluation of groups of features that can properly describe pollen in terms of shape, texture, size and apertures. The features are extracted on typical brightfield microscope images that enable…

Reconnaissance de formesSélection de caractéristiquesObject extractionClassificationPalynologyExtraction d’objetsAperturesPalynologiePattern recognitionFeature selectionFeature extractionBag of wordsExtraction de caractéristiquesSac-de-mots[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Non-linear RLS-based algorithm for pattern classification

2006

A new non-linear recursive least squares (RLS) algorithm is presented in the context of pattern classification problems. The algorithm incorporates the non-linearity of the filter's output in the updating rules of the classical RLS algorithm. The proposed method yields lower stationary error levels when compared to the standard LMS and RLS algorithms in a classical application of pattern classification, such as the channel equalization problem.

Recursive least squares filterSignal processingEqualizationContext (language use)Filter (signal processing)Computer Science::OtherNonlinear systemComputer Science::SoundControl and Systems EngineeringSignal ProcessingComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringAlgorithmSoftwareMathematicsSignal Processing
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Graph recursive least squares filter for topology inference in causal data processes

2017

In this paper, we introduce the concept of recursive least squares graph filters for online topology inference in data networks that are modelled as Causal Graph Processes (CGP). A Causal Graph Process (CGP) is an auto regressive process in the time series associated to different variables, and whose coefficients are the so-called graph filters, which are matrix polynomials with different orders of the graph adjacency matrix. Given the time series of data at different variables, the goal is to estimate these graph filters, hence the associated underlying adjacency matrix. Previously proposed algorithms have focused on a batch approach, assuming implicitly stationarity of the CGP. We propose…

Recursive least squares filterSignal processingMean squared errorComputer science020206 networking & telecommunications02 engineering and technologyCall graphNetwork topology0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)020201 artificial intelligence & image processingAdjacency matrixTime seriesAlgorithm2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
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Wavelet correlation filter for wide-angle seismic data

2002

A new filtering technique for single-fold wide-angle reflection/refraction seismic data is presented. The technique is based on the wavelet decomposition of a set of adjacent traces followed by coherence analysis. The filtering procedure consists of three steps. In the first, a wavelet decomposition of traces into different detail levels is performed. In the second, the coherence attributes for each level are evaluated by calculating cross-correlation functions of detail portions contained in a space–time moving window. Finally, the filtered traces are obtained as a weighted reconstruction of the trace details. Each weight is obtained from the coherence-attributes distribution estimated in …

Regional geologyGeophysicsWaveletCross-correlationGeochemistry and PetrologyMineralogyCoherence (signal processing)Seismic refractionFilter (signal processing)AlgorithmSeismic waveGeologyWavelet packet decompositionGeophysical Prospecting
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Image-based MRI Gradient Estimation

2017

In order to reduce geometric distortion phenomena in MR images, every MRI system main magnet undergoes a shimming process. Since this process aims at optimizing magnetic field homogeneity within a so-called uniformity sphere, image quality outside this sphere is neglected. Since the fields vary smoothly in space, MR signal-to-noise ratio is still non-zero just outside the uniformity region, but correction of MR image distortion fails due to lack of magnetic field knowledge outside it. We propose a novel algorithm for measuring all the fields involved in the generation of images. Our proposal is based on exploitation of the distortion which can be observed in images of a known phantom. The p…

RegistrationImage qualityComputer scienceBiomedical EngineeringBiophysicsImage enhancement/restoration (noise and artifact reduction)Signal-To-Noise Ratio01 natural sciencesGeometric distortionImaging phantom030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine0103 physical sciencesHomogeneity (physics)Gradient estimationRadiology Nuclear Medicine and imagingComputer visionMagnetic resonance imaging (MRI)010306 general physicsPhantoms Imagingbusiness.industrySettore ING-INF/03 - TelecomunicazioniImage EnhancementMagnetic Resonance ImagingMagnetic fieldMagnetArtificial intelligencebusinessAlgorithmsImage based
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Compartmental analysis of dynamic nuclear medicine data: Models and identifiability

2016

Compartmental models based on tracer mass balance are extensively used in clinical and pre-clinical nuclear medicine in order to obtain quantitative information on tracer metabolism in the biological tissue. This paper is the first of a series of two that deal with the problem of tracer coefficient estimation via compartmental modelling in an inverse problem framework. Specifically, here we discuss the identifiability problem for a general n-dimension compartmental system and provide uniqueness results in the case of two-compartment and three-compartment compartmental models. The second paper will utilize this framework in order to show how non-linear regularization schemes can be applied t…

Regularization (mathematics)Quantitative Biology - Quantitative Methods030218 nuclear medicine & medical imagingTheoretical Computer ScienceData modeling03 medical and health sciences0302 clinical medicinecompartmental analysis; identifiability; nuclear medicine dataTRACERFOS: Mathematicscompartmental analysisUniquenessMathematics - Numerical AnalysisMathematical PhysicsQuantitative Methods (q-bio.QM)Mathematicsbusiness.industryApplied MathematicsBiological tissueNumerical Analysis (math.NA)Inverse problemidentifiabilityComputer Science ApplicationsNonlinear systemnuclear medicine dataFOS: Biological sciencesSignal ProcessingIdentifiabilityNuclear medicinebusiness030217 neurology & neurosurgery
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Regularization operators for natural images based on nonlinear perception models.

2006

Image restoration requires some a priori knowledge of the solution. Some of the conventional regularization techniques are based on the estimation of the power spectrum density. Simple statistical models for spectral estimation just take into account second-order relations between the pixels of the image. However, natural images exhibit additional features, such as particular relationships between local Fourier or wavelet transform coefficients. Biological visual systems have evolved to capture these relations. We propose the use of this biological behavior to build regularization operators as an alternative to simple statistical models. The results suggest that if the penalty operator take…

Regularization perspectives on support vector machinesInformation Storage and RetrievalImage processingRegularization (mathematics)Pattern Recognition AutomatedOperator (computer programming)Artificial IntelligenceImage Interpretation Computer-AssistedCluster AnalysisComputer SimulationImage restorationMathematicsModels Statisticalbusiness.industryWavelet transformSpectral density estimationStatistical modelPattern recognitionNumerical Analysis Computer-AssistedSignal Processing Computer-AssistedImage EnhancementComputer Graphics and Computer-Aided DesignNonlinear DynamicsArtificial intelligencebusinessSoftwareAlgorithmsIEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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PO-350 MiRNAs and their relation to biological pathways in left- and right-sided colorectal cancer

2018

Introduction MicroRNAs (miRNAs) are involved in the regulation of gene expression in colorectal cancer (CRC), which has specific biological pathways that are predominant in either left- or right-sided CRC. However, it is unclear how miRNAs are associated with biological pathways in these two forms of CRC. Our hypothesis is that a comprehensive understanding of the fundamental biological signalling pathways in the two sides of CRC may aid in developing a decisive step towards precision medicine. We aim to clarify specific biological pathway differences of differentially expressed miRNAs between left- and right-sided CRC. Material and methods We extracted total RNA from 24 of left- and right-…

Regulation of gene expressionCancer ResearchSmall RNAColorectal cancerWnt signaling pathwayComputational biologyBiologyPrecision medicinemedicine.diseasedigestive system diseasesBiological pathwayOncologymicroRNAmedicinePI3K/AKT/mTOR pathwayESMO Open
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